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subprocess.run([sys.executable, \"-m\", \"pip\", \"install\", \"-q\", *_missing], check=False)\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from scipy import stats\n", "from huggingface_hub import HfApi, hf_hub_download\n", "from sklearn.metrics import roc_auc_score, cohen_kappa_score, average_precision_score\n", "from sklearn.model_selection import GroupKFold, StratifiedKFold\n", "from sklearn.ensemble import HistGradientBoostingClassifier\n", "from sklearn.inspection import permutation_importance\n", "\n", "SEED = 0\n", "rng_global = np.random.default_rng(SEED)\n", "pd.set_option(\"display.width\", 200)\n", "pd.set_option(\"display.max_columns\", 100)\n", "plt.rcParams.update({\"figure.dpi\": 110, \"font.size\": 9, \"axes.grid\": True,\n", " \"grid.alpha\": 0.25, \"axes.spines.top\": False, \"axes.spines.right\": False})\n", "\n", "REPO = \"Anthropic/claude-protein-binder-design\"\n", "BAR = \"=\" * 78\n", "\n", "def head(n, title):\n", " prefix = f\"{n}. \" if str(n) else \"\"\n", " print(f\"\\n{BAR}\\n {prefix}{title}\\n{BAR}\")\n", "\n", "head(1, \"TABLE DISCOVERY\")\n", "\n", "api = HfApi()\n", "repo_files = api.list_repo_files(REPO, repo_type=\"dataset\")\n", "\n", "TABLES = {}\n", "for f in repo_files:\n", " if f.startswith(\"data/tables/\") and f.endswith(\".parquet\"):\n", " key = f[len(\"data/tables/\"): -len(\".parquet\")].replace(\"/\", \"_\")\n", " TABLES[key] = f\n", "\n", "print(f\"Found {len(TABLES)} Parquet tables:\")\n", "for k in sorted(TABLES):\n", " print(f\" - {k:38s} {TABLES[k]}\")\n", "\n", "def load_table(name: str) -> pd.DataFrame:\n", " \"\"\"Load a subset by its viewer name, with a datasets-library fallback.\"\"\"\n", " if name in TABLES:\n", " return pd.read_parquet(hf_hub_download(REPO, TABLES[name], repo_type=\"dataset\"))\n", " from datasets import load_dataset\n", " return load_dataset(REPO, name, split=\"full\").to_pandas()\n", "\n", "ds = load_table(\"design_summary\")\n", "print(f\"\\ndesign_summary: {ds.shape[0]:,} rows x {ds.shape[1]} columns\")" ], "metadata": { "id": "fxwHOqkOzI1L" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "head(2, \"SCHEMA + EVALUABLE SET\")\n", "\n", "CALLS = {\"binder\", \"non_binder\"}\n", "tested = ds[\"adaptyv_binding\"].isin(CALLS) | ds[\"twist_binding\"].isin(CALLS)\n", "ev = ds[tested].copy()\n", "ev[\"y\"] = ev[\"binder_final\"].astype(int)\n", "\n", "print(f\"All designs : {len(ds):,}\")\n", "print(f\"Evaluable (>=1 vendor call): {len(ev):,}\")\n", "print(f\"Confirmed binders : {int(ev['y'].sum()):,} \"\n", " f\"({100 * ev['y'].mean():.1f}% base rate)\")\n", "print(f\"Never measured : {len(ds) - len(ev):,}\")\n", "\n", "print(\"\\nCategorical levels:\")\n", "for c in [\"design_model\", \"campaign\", \"generator\", \"sequence_design_method\", \"vendor_agreement\"]:\n", " vals = ds[c].astype(str).value_counts()\n", " print(f\" {c:24s} ({len(vals)}): {', '.join(vals.index[:6])}\"\n", " + (\" ...\" if len(vals) > 6 else \"\"))\n", "\n", "print(f\"\\nTargets ({ds['target'].nunique()}): {', '.join(sorted(ds['target'].unique()))}\")\n", "print(f\"Binder length: {ds.binder_length.min()}-{ds.binder_length.max()} aa \"\n", " f\"(median {ds.binder_length.median():.0f})\")\n", "\n", "head(3, \"HIT-RATE LANDSCAPE\")\n", "\n", "def wilson(k, n, z=1.96):\n", " if n == 0:\n", " return (np.nan, np.nan, np.nan)\n", " p = k / n\n", " d = 1 + z**2 / n\n", " c = (p + z**2 / (2 * n)) / d\n", " h = z * math.sqrt(p * (1 - p) / n + z**2 / (4 * n**2)) / d\n", " return p, max(0.0, c - h), min(1.0, c + h)\n", "\n", "def rate_table(df, by):\n", " rows = []\n", " for key, g in df.groupby(by, dropna=False):\n", " p, lo, hi = wilson(int(g.y.sum()), len(g))\n", " rows.append({by: key, \"n\": len(g), \"hits\": int(g.y.sum()),\n", " \"rate\": p, \"lo\": lo, \"hi\": hi})\n", " return pd.DataFrame(rows).sort_values(\"rate\", ascending=False).reset_index(drop=True)\n", "\n", "for dim in [\"design_model\", \"campaign\", \"generator\", \"sequence_design_method\"]:\n", " t = rate_table(ev, dim)\n", " print(f\"\\n--- hit rate by {dim} ---\")\n", " print(t.to_string(index=False,\n", " formatters={\"rate\": \"{:.3f}\".format, \"lo\": \"{:.3f}\".format, \"hi\": \"{:.3f}\".format}))\n", "\n", "tt = rate_table(ev, \"target\")\n", "fig, ax = plt.subplots(figsize=(9, 4.2))\n", "ax.bar(tt.target, tt.rate, color=\"#4C72B0\")\n", "ax.errorbar(tt.target, tt.rate,\n", " yerr=[(tt.rate - tt.lo).clip(lower=0), (tt.hi - tt.rate).clip(lower=0)],\n", " fmt=\"none\", ecolor=\"0.25\", capsize=3, lw=1)\n", "ax.axhline(ev.y.mean(), ls=\"--\", c=\"crimson\", lw=1, label=f\"pooled {ev.y.mean():.2f}\")\n", "ax.set_ylabel(\"experimental hit rate\"); ax.set_title(\"Hit rate by target (Wilson 95% CI)\")\n", "ax.tick_params(axis=\"x\", rotation=55); ax.legend(); plt.tight_layout(); plt.show()\n", "\n", "print(\"\\nRead this plot as the dominant effect size in the dataset: target choice \"\n", " \"swamps generator choice. Any model comparison that does not stratify by \"\n", " \"target is mostly measuring which targets that model was pointed at.\")" ], "metadata": { "id": "yi_IVvWlzIsr" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "head(4, \"PER-PREDICTOR DISCRIMINATIVE POWER\")\n", "\n", "PREDICTORS = sorted({c[len(\"ipsae_min_\"):] for c in ds.columns if c.startswith(\"ipsae_min_\")})\n", "print(f\"Predictors ({len(PREDICTORS)}): {', '.join(PREDICTORS)}\")\n", "\n", "def auc_ci(y, s, n_boot=300, seed=SEED):\n", " s = np.asarray(s, dtype=float); y = np.asarray(y, dtype=int)\n", " m = ~np.isnan(s)\n", " y, s = y[m], s[m]\n", " if len(y) < 30 or len(np.unique(y)) < 2:\n", " return dict(auc=np.nan, lo=np.nan, hi=np.nan, n=len(y), ap=np.nan)\n", " base = roc_auc_score(y, s)\n", " ap = average_precision_score(y, s)\n", " rng = np.random.default_rng(seed)\n", " idx, boots = np.arange(len(y)), []\n", " for _ in range(n_boot):\n", " b = rng.choice(idx, len(idx), replace=True)\n", " if len(np.unique(y[b])) > 1:\n", " boots.append(roc_auc_score(y[b], s[b]))\n", " lo, hi = (np.percentile(boots, [2.5, 97.5]) if boots else (np.nan, np.nan))\n", " return dict(auc=base, lo=lo, hi=hi, n=len(y), ap=ap)\n", "\n", "rows = []\n", "for p in PREDICTORS:\n", " for metric in [\"ipsae_min\", \"sc_dockq\"]:\n", " col = f\"{metric}_{p}\"\n", " if col in ev.columns:\n", " r = auc_ci(ev.y, ev[col])\n", " rows.append({\"predictor\": p, \"metric\": metric, **r})\n", "\n", "perf = pd.DataFrame(rows)\n", "piv = perf.pivot(index=\"predictor\", columns=\"metric\", values=\"auc\").sort_values(\"ipsae_min\", ascending=False)\n", "print(\"\\nAUC vs experimental binder_final:\")\n", "print(perf.sort_values(\"auc\", ascending=False).to_string(\n", " index=False, formatters={c: \"{:.3f}\".format for c in [\"auc\", \"lo\", \"hi\", \"ap\"]}))\n", "\n", "fig, ax = plt.subplots(figsize=(9, 4.2))\n", "x = np.arange(len(piv)); w = 0.38\n", "for i, (metric, colr) in enumerate([(\"ipsae_min\", \"#4C72B0\"), (\"sc_dockq\", \"#DD8452\")]):\n", " sub = perf[perf.metric == metric].set_index(\"predictor\").reindex(piv.index)\n", " lo_err = (sub.auc - sub.lo).clip(lower=0).fillna(0)\n", " hi_err = (sub.hi - sub.auc).clip(lower=0).fillna(0)\n", " ax.bar(x + (i - 0.5) * w, sub.auc, w, label=metric, color=colr)\n", " ax.errorbar(x + (i - 0.5) * w, sub.auc,\n", " yerr=[lo_err, hi_err], fmt=\"none\", ecolor=\"0.3\", capsize=2, lw=0.9)\n", "ax.axhline(0.5, ls=\"--\", c=\"crimson\", lw=1)\n", "ax.set_xticks(x); ax.set_xticklabels(piv.index, rotation=45, ha=\"right\")\n", "ax.set_ylabel(\"AUC\"); ax.set_ylim(0.35, None)\n", "ax.set_title(\"In-silico score vs wet-lab binding, by structure predictor\")\n", "ax.legend(); plt.tight_layout(); plt.show()\n", "\n", "print(\"Interpretation: AUCs land well above chance but far below the ~0.9 you \"\n", " \"would need to trust a single filter. That gap is the entire practical \"\n", " \"reason this dataset exists.\")\n", "\n", "head(5, \"CONSENSUS SCORING\")\n", "\n", "ips_cols = [f\"ipsae_min_{p}\" for p in PREDICTORS if f\"ipsae_min_{p}\" in ev.columns]\n", "dq_cols = [f\"sc_dockq_{p}\" for p in PREDICTORS if f\"sc_dockq_{p}\" in ev.columns]\n", "\n", "def pct_rank(df, cols):\n", " return df[cols].rank(pct=True, na_option=\"keep\")\n", "\n", "R_ips, R_dq = pct_rank(ev, ips_cols), pct_rank(ev, dq_cols)\n", "ev[\"cons_ipsae\"] = R_ips.mean(axis=1)\n", "ev[\"cons_dockq\"] = R_dq.mean(axis=1)\n", "ev[\"cons_all\"] = pd.concat([R_ips, R_dq], axis=1).mean(axis=1)\n", "ev[\"cons_median\"] = pd.concat([R_ips, R_dq], axis=1).median(axis=1)\n", "ev[\"cons_min\"] = pd.concat([R_ips, R_dq], axis=1).min(axis=1)\n", "ev[\"cons_disagree\"] = pd.concat([R_ips, R_dq], axis=1).std(axis=1)\n", "\n", "best_single = perf.loc[perf.auc.idxmax()]\n", "print(f\"Best single column: {best_single.metric}_{best_single.predictor} AUC={best_single.auc:.3f}\")\n", "print()\n", "for name in [\"cons_ipsae\", \"cons_dockq\", \"cons_all\", \"cons_median\", \"cons_min\", \"cons_disagree\"]:\n", " r = auc_ci(ev.y, ev[name])\n", " print(f\" {name:16s} AUC={r['auc']:.3f} [{r['lo']:.3f}, {r['hi']:.3f}] AP={r['ap']:.3f}\")\n", "\n", "corr = ev[ips_cols].corr(method=\"spearman\")\n", "fig, ax = plt.subplots(figsize=(6.2, 5.2))\n", "im = ax.imshow(corr.values, cmap=\"viridis\", vmin=0, vmax=1)\n", "lbl = [c.replace(\"ipsae_min_\", \"\") for c in ips_cols]\n", "ax.set_xticks(range(len(lbl))); ax.set_xticklabels(lbl, rotation=90)\n", "ax.set_yticks(range(len(lbl))); ax.set_yticklabels(lbl)\n", "ax.set_title(\"Spearman correlation between predictors (ipSAE)\")\n", "ax.grid(False); fig.colorbar(im, shrink=0.8); plt.tight_layout(); plt.show()\n", "\n", "print(\"\\nIf every off-diagonal cell were ~1.0 there would be no ensemble gain to \"\n", " \"harvest. The moderate correlations are why cons_all typically edges out \"\n", " \"the best single predictor — and why disagreement itself carries signal.\")" ], "metadata": { "id": "5C2akpfPzIiS" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "head(6, \"BUDGET CURVES (precision@N)\")\n", "\n", "def budget_curve(df, score_col, max_n=400):\n", " d = df[[score_col, \"y\"]].dropna().sort_values(score_col, ascending=False)\n", " hits = d.y.values.cumsum()\n", " n = np.arange(1, len(d) + 1)\n", " k = min(max_n, len(d))\n", " return n[:k], (hits / n)[:k]\n", "\n", "fig, ax = plt.subplots(figsize=(8, 4.4))\n", "best_col = f\"{best_single.metric}_{best_single.predictor}\"\n", "for col, lab, style in [(best_col, f\"best single ({best_col})\", \"-\"),\n", " (\"cons_all\", \"consensus (rank-avg, all)\", \"-\"),\n", " (\"cons_min\", \"consensus (unanimity/min)\", \"--\")]:\n", " n, prec = budget_curve(ev, col)\n", " ax.plot(n, prec, style, lw=1.8, label=lab)\n", "ax.axhline(ev.y.mean(), ls=\":\", c=\"crimson\", lw=1.4, label=f\"random baseline ({ev.y.mean():.2f})\")\n", "ax.set_xlabel(\"designs ordered for wet-lab testing (N, best-first)\")\n", "ax.set_ylabel(\"hit rate among top N\"); ax.set_title(\"How much does in-silico triage buy you?\")\n", "ax.legend(); plt.tight_layout(); plt.show()\n", "\n", "print(\"Enrichment at small budgets:\")\n", "for N in [25, 50, 100, 200]:\n", " line = f\" N={N:4d} | random {ev.y.mean():.3f}\"\n", " for col, lab in [(best_col, \"best-single\"), (\"cons_all\", \"consensus\")]:\n", " n, prec = budget_curve(ev, col, max_n=N)\n", " line += f\" | {lab} {prec[-1]:.3f} ({prec[-1] / ev.y.mean():.2f}x)\"\n", " print(line)\n", "\n", "head(7, \"VENDOR CONCORDANCE\")\n", "\n", "both = ev[ev.adaptyv_binding.isin(CALLS) & ev.twist_binding.isin(CALLS)]\n", "ct = pd.crosstab(both.adaptyv_binding, both.twist_binding)\n", "print(f\"Designs with calls from BOTH vendors: {len(both):,}\\n\")\n", "print(ct.to_string())\n", "\n", "if len(both) > 10:\n", " kappa = cohen_kappa_score(both.adaptyv_binding, both.twist_binding)\n", " agree = (both.adaptyv_binding == both.twist_binding).mean()\n", " print(f\"\\nRaw agreement: {agree:.3f} Cohen's kappa: {kappa:.3f}\")\n", " print(\"Kappa well under 1.0 means part of the 'unpredictable' variance above \"\n", " \"is assay disagreement, not model failure.\")\n", "\n", "kd = ev[[\"adaptyv_kd_nM\", \"twist_kd_nM\"]].dropna()\n", "kd = kd[(kd > 0).all(axis=1)]\n", "if len(kd) > 10:\n", " rho, pv = stats.spearmanr(kd.adaptyv_kd_nM, kd.twist_kd_nM)\n", " fig, ax = plt.subplots(figsize=(4.8, 4.6))\n", " ax.scatter(kd.adaptyv_kd_nM, kd.twist_kd_nM, s=16, alpha=0.6, c=\"#4C72B0\", edgecolor=\"none\")\n", " lims = [min(kd.min()) * 0.5, max(kd.max()) * 2]\n", " ax.plot(lims, lims, \"k--\", lw=1)\n", " ax.set_xscale(\"log\"); ax.set_yscale(\"log\")\n", " ax.set_xlabel(\"Adaptyv KD (nM)\"); ax.set_ylabel(\"Twist KD (nM)\")\n", " ax.set_title(f\"Cross-vendor KD, n={len(kd)}, Spearman rho={rho:.2f}\")\n", " plt.tight_layout(); plt.show()\n", " med_ratio = np.median(kd.twist_kd_nM / kd.adaptyv_kd_nM)\n", " print(f\"Median KD ratio (Twist/Adaptyv): {med_ratio:.2f}x -> systematic format offset, \"\n", " \"so treat absolute KD across vendors as ordinal, not interchangeable.\")" ], "metadata": { "id": "YPm7U5mczIfa" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "head(8, \"EXPRESSION CONFOUND\")\n", "\n", "if \"twist_expression_mg_per_mL\" in ev.columns:\n", " g = ev.dropna(subset=[\"twist_expression_mg_per_mL\"])\n", " a = g.loc[g.y == 1, \"twist_expression_mg_per_mL\"]\n", " b = g.loc[g.y == 0, \"twist_expression_mg_per_mL\"]\n", " if len(a) > 5 and len(b) > 5:\n", " u, pv = stats.mannwhitneyu(a, b)\n", " print(f\"Titer (mg/mL) binders median {a.median():.2f} (n={len(a)}) | \"\n", " f\"non-binders {b.median():.2f} (n={len(b)}) Mann-Whitney p={pv:.2e}\")\n", " r = auc_ci(g.y, g.twist_expression_mg_per_mL)\n", " print(f\"AUC of raw expression titer alone as a 'binder' predictor: {r['auc']:.3f}\")\n", "\n", " fig, axes = plt.subplots(1, 2, figsize=(9, 3.6))\n", " axes[0].hist([b, a], bins=25, label=[\"non-binder\", \"binder\"],\n", " color=[\"#BBBBBB\", \"#4C72B0\"], density=True)\n", " axes[0].set_xlabel(\"Twist titer (mg/mL)\"); axes[0].set_ylabel(\"density\"); axes[0].legend()\n", " axes[0].set_title(\"Expression by outcome\")\n", "\n", " if \"adaptyv_expression\" in ev.columns:\n", " ex = ev.groupby(ev.adaptyv_expression.astype(str)).y.agg([\"mean\", \"size\"])\n", " ex = ex[ex[\"size\"] >= 10].sort_values(\"mean\")\n", " axes[1].barh(ex.index, ex[\"mean\"], color=\"#DD8452\")\n", " axes[1].set_xlabel(\"hit rate\"); axes[1].set_title(\"Hit rate by Adaptyv expression class\")\n", " plt.tight_layout(); plt.show()\n", "\n", "print(\"\\nTakeaway: if expression alone scores meaningfully above 0.5, then part of \"\n", " \"every AUC in section 4 is a solubility signal riding along. To isolate \"\n", " \"interface quality, re-run section 4 restricted to designs that expressed.\")\n", "\n", "expressed = ev[ev.adaptyv_expression.astype(str).isin([\"medium\", \"high\"])] if \"adaptyv_expression\" in ev.columns else ev\n", "if len(expressed) > 100:\n", " r_all = auc_ci(ev.y, ev.cons_all)\n", " r_exp = auc_ci(expressed.y, expressed.cons_all)\n", " print(f\" consensus AUC, all evaluable : {r_all['auc']:.3f} (n={r_all['n']})\")\n", " print(f\" consensus AUC, expressed only : {r_exp['auc']:.3f} (n={r_exp['n']})\")\n", "\n", "head(9, \"EPITOPE CONVERGENCE\")\n", "\n", "def parse_epitope(s):\n", " if not isinstance(s, str) or not s.strip():\n", " return frozenset()\n", " out = set()\n", " for tok in s.split(\";\"):\n", " tok = tok.strip()\n", " if not tok:\n", " continue\n", " out.add(tok.split(\":\")[-1])\n", " return frozenset(out)\n", "\n", "ev[\"epi\"] = ev[\"epitope_residues\"].apply(parse_epitope)\n", "\n", "def mean_pairwise_jaccard(sets, max_pairs=4000, seed=SEED):\n", " sets = [s for s in sets if len(s) > 0]\n", " if len(sets) < 2:\n", " return np.nan\n", " pairs = list(itertools.combinations(range(len(sets)), 2))\n", " rng = np.random.default_rng(seed)\n", " if len(pairs) > max_pairs:\n", " pairs = [pairs[i] for i in rng.choice(len(pairs), max_pairs, replace=False)]\n", " vals = []\n", " for i, j in pairs:\n", " u = len(sets[i] | sets[j])\n", " vals.append(len(sets[i] & sets[j]) / u if u else 0.0)\n", " return float(np.mean(vals))\n", "\n", "rows = []\n", "for tgt, g in ev.groupby(\"target\"):\n", " B = g.loc[g.y == 1, \"epi\"].tolist()\n", " N = g.loc[g.y == 0, \"epi\"].tolist()\n", " if len(B) >= 3 and len(N) >= 3:\n", " rows.append({\"target\": tgt, \"n_bind\": len(B), \"n_non\": len(N),\n", " \"J_binders\": mean_pairwise_jaccard(B),\n", " \"J_nonbinders\": mean_pairwise_jaccard(N)})\n", "epi = pd.DataFrame(rows)\n", "if len(epi):\n", " epi[\"delta\"] = epi.J_binders - epi.J_nonbinders\n", " print(epi.sort_values(\"delta\", ascending=False).to_string(\n", " index=False, formatters={c: \"{:.3f}\".format for c in [\"J_binders\", \"J_nonbinders\", \"delta\"]}))\n", " w = stats.wilcoxon(epi.J_binders, epi.J_nonbinders) if len(epi) >= 6 else None\n", " if w:\n", " print(f\"\\nPaired Wilcoxon across targets: p={w.pvalue:.4f} \"\n", " f\"(binders more epitope-convergent than failures?)\")\n", "\n", " tgt = epi.sort_values(\"n_bind\", ascending=False).target.iloc[0]\n", " sub = ev[ev.target == tgt]\n", " freq_b = pd.Series([r for s in sub[sub.y == 1].epi for r in s]).value_counts()\n", " freq_n = pd.Series([r for s in sub[sub.y == 0].epi for r in s]).value_counts()\n", " top = freq_b.head(18).index\n", " fig, ax = plt.subplots(figsize=(9, 3.8))\n", " xx = np.arange(len(top))\n", " ax.bar(xx - 0.2, (freq_b.reindex(top).fillna(0) / max(1, (sub.y == 1).sum())), 0.4,\n", " label=\"binders\", color=\"#4C72B0\")\n", " ax.bar(xx + 0.2, (freq_n.reindex(top).fillna(0) / max(1, (sub.y == 0).sum())), 0.4,\n", " label=\"non-binders\", color=\"#BBBBBB\")\n", " ax.set_xticks(xx); ax.set_xticklabels(top, rotation=70, ha=\"right\")\n", " ax.set_ylabel(\"fraction of designs contacting\"); ax.set_title(f\"Epitope usage on {tgt}\")\n", " ax.legend(); plt.tight_layout(); plt.show()" ], "metadata": { "id": "di8pVoprzIci" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "c64cb7a9f45047a580c345ccc551277d", "9c8f80ffcadc4b66bf92d396b22da2d4", "13e7c8506f45466fbbf1d9ed416ef545", "eb735830f64443c39b5471ae657d8739", "7c1966a1fe9547b681610aa89a70d33e", "e19ed5522e6e443ea719875343a120b6", "419bedc41e894215a0bd1b90038e5c8d", "936ae77d964a4ceda818cbb0850f432a", "ef170eefb90d49b2a91812ad35576478", "4604da5dd3f64b518f79bbcc085b6841", "6d172719208c4ebca11da4ab5a36516c", "237d1e3455254148b2a5205fd3b23f89", "a8bc63ba1eb2418a844f5c2dd0178a79", "730e23bff031446fac0d396c8e8cd768", "4e36dc54aab944918903fe42ee9b6a9f", "525f5615b78e4fa4a34c7f7a20596c1b", "b3c56f9c8c14480daed29a43b7838c03", "effb107dee32462d92c290b443beb3af", "0849fad43e6748f08f7c191466a4389b", "dd67b5d916014b45bc87c26bbd56c022", "c1096d2087e14a7a9eb9f8ea674c1472", "ecc06c34430f48d49dbf779435212dfd" ] }, "id": "5oPodcvzyo10", "outputId": "1b3fb479-46e1-4a43-c1e7-1c272e348b9d" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "==============================================================================\n", " 1. TABLE DISCOVERY\n", "==============================================================================\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n", "WARNING:huggingface_hub.utils._http:Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Found 19 Parquet tables:\n", " - adaptyv_fit_curves data/tables/adaptyv/fit_curves.parquet\n", " - adaptyv_fits_all_models data/tables/adaptyv/fits_all_models.parquet\n", " - adaptyv_reads data/tables/adaptyv/reads.parquet\n", " - adaptyv_replicates data/tables/adaptyv/replicates.parquet\n", " - adaptyv_results data/tables/adaptyv/results.parquet\n", " - column_dictionary data/tables/column_dictionary.parquet\n", " - design_summary data/tables/design_summary.parquet\n", " - insilico_cofold_predictions data/tables/insilico/cofold_predictions.parquet\n", " - insilico_epitope_residue_contacts data/tables/insilico/epitope_residue_contacts.parquet\n", " - insilico_provenance_steps data/tables/insilico/provenance_steps.parquet\n", " - insilico_provenance_summary data/tables/insilico/provenance_summary.parquet\n", " - insilico_target_constructs data/tables/insilico/target_constructs.parquet\n", " - twist_expression_titer_sec data/tables/twist/expression_titer_sec.parquet\n", " - twist_fits data/tables/twist/fits.parquet\n", " - twist_raw_segments data/tables/twist/raw_segments.parquet\n", " - twist_vendor_software_fits data/tables/twist/vendor_software_fits.parquet\n", " - wetlab_antigens_and_controls data/tables/wetlab/antigens_and_controls.parquet\n", " - wetlab_measurements data/tables/wetlab/measurements.parquet\n", " - wetlab_summary data/tables/wetlab/summary.parquet\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "data/tables/design_summary.parquet: reconstructing file: 0%| | 0.00B / 518kB " ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "c64cb7a9f45047a580c345ccc551277d" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "data/tables/design_summary.parquet: downloading bytes: | 0.00B " ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "237d1e3455254148b2a5205fd3b23f89" } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "design_summary: 1,440 rows x 65 columns\n", "\n", "==============================================================================\n", " 2. SCHEMA + EVALUABLE SET\n", "==============================================================================\n", "All designs : 1,440\n", "Evaluable (>=1 vendor call): 1,314\n", "Confirmed binders : 354 (26.9% base rate)\n", "Never measured : 126\n", "\n", "Categorical levels:\n", " design_model (2): Mythos Preview, Opus 4.8\n", " campaign (3): multi_target, single_target, single_target_supplementary\n", " generator (10): PXDesign, RFdiffusion3, Genie3, BoltzGen, FreeBindCraft (BindCraft), RFdiffusion ...\n", " sequence_design_method (4): SolubleMPNN, Caliby (SolubleCaliby), designed jointly by the structure model (native co-design), ProteinMPNN\n", " vendor_agreement (8): neither_bind, both_bind, None, adaptyv_only_bind, twist_only_bind, adaptyv_only_tested ...\n", "\n", "Targets (16): 15-PGDH, BBF-14, BHRF1, Cas9, EGFR, IL-7Ra, Latent GDF-8, MBP, Mature GDF-8, Nipah-G, PD-L1, RBX1, TNFa, TREM2, TrkA, VEGF-A\n", "Binder length: 50-120 aa (median 80)\n", "\n", "==============================================================================\n", " 3. HIT-RATE LANDSCAPE\n", "==============================================================================\n", "\n", "--- hit rate by design_model ---\n", " design_model n hits rate lo hi\n", "Mythos Preview 836 262 0.313 0.283 0.346\n", " Opus 4.8 478 92 0.192 0.160 0.230\n", "\n", "--- hit rate by campaign ---\n", " campaign n hits rate lo hi\n", " single_target 505 160 0.317 0.278 0.359\n", " multi_target 779 192 0.246 0.217 0.278\n", "single_target_supplementary 30 2 0.067 0.018 0.213\n", "\n", "--- hit rate by generator ---\n", " generator n hits rate lo hi\n", "FreeBindCraft (BindCraft) 135 58 0.430 0.349 0.514\n", " Proteina-Complexa 99 34 0.343 0.257 0.441\n", " BoltzGen 134 37 0.276 0.207 0.357\n", " RFdiffusion3 267 72 0.270 0.220 0.326\n", " PXDesign 358 86 0.240 0.199 0.287\n", " Genie3 185 41 0.222 0.168 0.287\n", " RFdiffusion 118 26 0.220 0.155 0.303\n", " BoltzDesign1 2 0 0.000 0.000 0.658\n", " FoldCraft 14 0 0.000 0.000 0.215\n", " Protein Hunter 2 0 0.000 0.000 0.658\n", "\n", "--- hit rate by sequence_design_method ---\n", " sequence_design_method n hits rate lo hi\n", "designed jointly by the structure model (native co-design) 50 17 0.340 0.224 0.478\n", " SolubleMPNN 1132 317 0.280 0.255 0.307\n", " Caliby (SolubleCaliby) 111 19 0.171 0.112 0.252\n", " ProteinMPNN 21 1 0.048 0.008 0.227\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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YWJrrUmYKP3r0KE6ePInQ0FDdupo1a0Kj0eC3337D5cuXERwcnKHnTZE/f34MGjQIgwYNwuPHj1G5cmV8+eWXaNSoka7l+tq1a3qvcVxcHO7fv29Q8f02KpVKryfI/v37ASDNYRCvSk5Oxt27d1G1atU3brN161ZcuXIF27dvBwA8ePAA+fPn160vUKAA7t+//9bnadasGU6ePIkff/wRHTt2fFc6b5TyfpcpU8bgfRARWSuOsSYionTJmTMngJczixsjpXXw1dbAZ8+eYc2aNWk+Z1rP165dO/z+++9pjhF+/Phxuloajx07hgsXLuju37p1C7/99hsaN26st12lSpVQrlw5rFixAjt27EDnzp3TVYS+6fXKSP5v0qhRI/z77796Y4UTExOxcuVKve0qV66MYsWKYfbs2am6nAP6XeYz+v7WqFEDFy9eRHJycqp11apVg52dHVauXIno6OhU45eLFy+OOXPmQKvVprpc17toNJpU49Dd3d1RsGBBJCYmAgDq168Pe3t7fP3113qv85IlS5CcnGzU+Ph3efToEWbMmIFGjRrpFaBpDU+YNWsWEhMT31joJyQkYNSoUQgNDYWLiwuAlzPj37x5E2q1GgBw5coVeHl5vTWmgQMHwtPTEyNHjsStW7dSrb9//z5mzZr1ztzOnDmDPHnypOpiT0REbLEmIqJ08vf3B/CyW2qjRo2gUqnQqVOnDO+nYcOGsLe3R/PmzTFgwADExsZi5cqV8PDwQERERKrnXLhwIb788kvdON169ephzJgx2L59Oxo1aoQ+ffrAz88PMTExuHDhArZt24bnz5+nugzU68qWLYuGDRti6NChUKlUWLx4MRwcHHSX9npV9+7dMXbsWABIdzfwlNfr888/R6dOnWBnZ4fmzZtnKP83GTBgABYtWoQOHTpg2LBh8PLywoYNG3Qt7SmFv0qlwooVK9C0aVOUL18ePXv2RP78+XHv3j3s3bsXJUqU0F1eK6Pvb8uWLTF16lQcPXo0Vcusk5MTKlWqhJMnTyJ37typuubXrFlT97wZnbjs+fPnKFiwINq2bYuKFSvC2dkZBw8exMmTJzFnzhwAL4v3zz77DJMnT0bTpk3RtGlT/P3331ixYgUaNGiAZs2aZeg536Z27dqoXbs2SpQogcjISCxfvhxarVZ3iawURYoUQadOnVCuXDk4ODjg0KFD2LZtG2rXro0uXbqkue8ZM2bA09MTvXr10i1r0qQJhgwZgi5duqBmzZqYOnUq+vbt+9YY8+TJgx9//BHNmjVDxYoV0b17d1SqVAlarRanT5/Gpk2b0vWa7Nu3Dy1atOAYayKitJhxRnIiIsoiKZfbOnfuXJrrX7+sVVqX29JoNDJs2DDJly+fKIryzkszFSlSRFq2bJnmuh07dkiFChXE0dFRfHx8ZMaMGbJ69epUl6eKioqS5s2bi7Ozc6pLgj179kzGjBkjxYoVEzs7O/Hw8JA6derIggUL9C6xlBYAMmzYMFm3bp2UKFFCHBwcpGrVqnLixIk0t793757u0kgZMW3aNPH29hYbGxu93NKb/9tew9u3b0vTpk0lR44cki9fPhk5cqRs27ZNAMgff/yht+2ZM2ekZcuWkidPHnFwcJCiRYtK165d5dixY7ptMvr+ioiUL19eBg4cmOa6ESNGCABp2LBhqnVLliwRAKkuLyby7sttvXjxQkaPHi0VK1YUZ2dnyZkzp1SsWFGWLFmSal9ff/21lCpVSuzs7KRAgQIyYsQIiY2N1dvmTa9xYGBgmpd6e93QoUOlaNGiYm9vL56entKnTx+5f/9+qu369u0rZcqUkVy5com9vb188MEH8sUXX6R56TURkX///VecnJxSvZciIr/++quULl1aXF1dpUePHhIXF/fOOEVefo6HDRsmJUuWFAcHB8mZM6dUrVpVZs2apfe6pHW5rStXruhdyo2IiPQpIunoL0dERPQee/jwIQoUKIDp06dj1KhR5g7njebPn48RI0bg3r178Pb2zvTnW7duHYYPH47w8HCTXM6Jsq+QkBD8/vvv+Ouvv8wdChFRtsQx1kRERO+wevVqAHhjl11zePUaycDLMdbLly9HyZIls6SoBl52i/fy8krV7ZmsS3R0NFauXImpU6eaOxQiomyLY6yJiIje4ODBg/jnn38QGhqK9u3bo0CBAuYOSadly5YoWrQo/Pz88PTpU2zYsAFXr17Fhg0bsiwGlUqFK1euZNnzkXm4ubmZ5DrYRETWjF3BiYiI3uCjjz7CiRMnULt2bWzYsEHvMkfmNnfuXHzzzTf4999/odFoULZsWYwZMwYdOnQwd2hERETvHRbWREREREREREbgGGsiIiIiIiIiI7CwJiIiIiIiIjICC2siIiIiIiIiI7zXhbVarca9e/egVqvNHQoRERERERFZqPe6sI6MjEShQoUQGRlp7lCynEajwePHj6HRaMwdSqZgfpbLmnMDmJ+ls+b8rDk3gPlZOmvOz5pzA5ifpbP2/EzpvS6siYiIiIiIiIzFwpqIiIiIiIjICCysiYiIiIiIiIzAwpqIiIiIiIjICCysiYiIiIiIiIxga+4AiIiIiIiIspJarcbjx4+RlJQErVZr8H5EBC9evMDz58+hKIoJI8werDk/lUqF3Llzw8XFxST7Y2FNRERERETvjbi4ONy/fx8ajQYODg6wsTG8E6+iKLC3t7e6ojOFNeeXmJiI2NhYADBJcc3CmoiIiIiI3hvR0dEAgKJFi8LR0dGofYkI1Go1bG1trbL4tOb8NBoNbt++jWfPnpmksOYYayIiIiIiem+o1WrY29sbXVSTZVOpVLCzs4NGozHJ/lhYExERERERERmBhTURERERERGREVhYExERERERERmBhTURERERERHh8OHDUBRFN1u2odzd3bF27VrTBGUhOCv4eyI4OFjv/ptm+Fu4cGFWh0ZERERERO+ZxYsXY9asWYiMjISfnx8WLlyIqlWrvnH7lStXYv369fj777+hKAqqVKmCadOmoUqVKrpt3jRz+cyZMzF69GiT5/Aqtli/p8LCwhAeHm7uMIiIiIiI6D2zefNmhISEYOLEiTh79iwqVKiARo0a4fHjx298zOHDh9G5c2ccOnQIJ06cgLe3Nxo0aICIiAjdNhEREXq31atXQ1EUtG3bNtNzYmH9nli4cKHerWjRoihcuDAWLFigt5yIiIiIiLKfjz76CMOGDcPgwYORO3dueHh4IDQ0VG+bO3fuoHnz5siZMydcXV3RrVs33XW7AUCr1WLixInw9vaGg4MDqlSpgiNHjrz1eY8dO4batWsjR44cKFKkCMaMGYMXL17o1kdGRqJZs2bIkSMHSpQogW3btr0zl7lz56J///7o3bs3fH19sWzZMuTIkeOt3cc3bNiAwYMHw8/PD6VLl8aqVaug0Whw6NAh3TZeXl56t+3bt6Nu3booVqzYO2MyFruCExERERERAbjfdHCqZTkCqyDPmD4AgIjun0H73zPdOgFgV7Y4PGaEAAAeDg1F8q27eo+39faA54pJAIDHkxbjxel/AADeu5ZkOL7Vq1dj0KBBOHXqFE6cOIFBgwahRIkSaN++PbRaLVq2bAk3NzccO3YMCQkJGDBgAHr37o2ff/4ZADBv3jwsWLAAK1euRPny5bF06VI0adIE169fh7e3d6rnu3XrFlq0aIGvvvoK69atQ0REBAYNGoTk5GTMmzcPANCzZ088evRIV6AHBwfj+fPnb8whKSkJZ86cwfjx43XLbGxsUL9+fZw8eTLdr0V8fDySk5ORJ0+eNNdHRUVh165dWLduXbr3aQwW1kRERERERBagWLFimDlzJgCgVKlSOHPmDObNm4f27dtj//79uHz5Mv79918UKFAAAPDNN98gICAAN27cQMmSJTFnzhz873//Q/v27QEA8+fPx/79+7FkyRJ89dVXqZ4vNDQU3bp1Q3BwMBRFQYkSJTB79my0bdsWc+fOxfXr17F3716cPXsWlSpVAvBy7PTbxko/fvwYGo0Gnp6eess9PT1x8+bNdL8W48aNQ6FChVCvXr00169btw7Ozs5o06ZNuvdpDBbWREREREREeHcrcv5v9btep0wInMLj68/e+nj3SUMMDw5AQECA3v0aNWpgw4YNAIArV67Ax8dHV1QDQNWqVWFvb48rV67Aw8MDERERqFWrlm69oiioWbMmrly5kubzXbx4ERcvXsS3336rW6bVapGQkIDIyEhcvXoVDg4O8PPz06339/eHvb29UXm+y8yZM7Fp0yYcOXLkjc+1evVqdO3aFY6OjpkaSwoW1kRERERERJRKbGwsBg0ahCFDhqSacTtfvnwG7dPd3R0qlQpRUVF6y6OiouDl5fXOx8+ePRvTpk3D/v37Ua5cuTS3OXr0KK5du4bNmzcbFKMhOHkZERERERGRBTh16pTe/T/++ANlypQBAJQpUwZ37tzBgwcPdOtPnz6NpKQklClTBrlz50b+/Plx/Phx3XoRwYkTJ+Dr65vm81WqVAmXL19GiRIlUt1sbW1RunRpvHjxAufPn9c95uzZs0hKSnpjDvb29vD398e+fft0y7RaLQ4cOIAaNWq8Nf+ZM2di6tSp2LNnj95ltl73zTffwN/fHxUrVnzr/kyJhTUREREREZEFuHXrFsaNG4fr169j3bp1WLVqFYYNGwYAqF+/Pnx9fdG1a1ecO3cOJ06cwKeffoqWLVuiZMmSAICRI0di2rRp+OGHH3Dt2jUMHz4cd+7cweDBqSdtA4DRo0fj6NGjGDZsGC5cuIDr16/jxx9/1F0TulSpUqhfvz769euH06dP4/Tp0wgKCnpnV/CQkBCsWLEC69atw5UrVzBo0CDEx8ejV69eum169OiBzz77v671M2bMwBdffIHVq1fDx8cHkZGRiIyMRGxsrN6+Y2JisHXrVvTt2zfDr68x2BWciIiIiIjIAvTp0wf//fcfqlSpAgcHB4wfPx4dO3YE8HJm7e3btyM4OBi1a9eGra0tmjdvrndJ3REjRiAmJgZDhw7FkydPUL58eezevVtvXPar/Pz8sG/fPkyaNAk1a9aESqVCiRIl0LNnT90269evx6effooPP/wQ+fPnx6xZszBw4MC35tGxY0c8evQIEyZMQGRkJPz8/LBnzx64u7vrtgkPD4eNzf+1Ay9duhRJSUlo166d3r4mTpyISZMm6e5v2rQJIoLOnTu/+wU1IUVEJEufMRu5d+8eChUqhLt376JgwYLmDidLBQUFQa1WY/HixVCpVOYOx+Q0Gg2io6Ph5ubG/CyMNecGMD9LZ835WXNuAPOzdNacnzXnBmTP/O7cuQMA8PHxMXpfKZOX2draphqDbGofffQRqlSpgtmzZ2fq87wqK/MzB1N+FtgVnIiIiIiIiMgILKyJiIiIiIiIjMAx1kRERERERNnc4cOHzR0CvQVbrImIiIiIiIiMwMKaiIiIiIjeGyqVChqNxtxhUDag1Wr1Zh43BgtrIiIiIiJ6bzg6OiIpKQlPnjwxdyhkRomJiXjx4sU7r7mdXhxjTURERERE7w13d3e8ePECDx8+xNOnT42+DJgpWz2zI2vNLykpCSqVSu/a2cawvleIiIiIiIjoDRRFgbe3N9zd3Y1urRQRJCUlQURMFF32Ys35OTk5wdvbG7a2pmlrZos1ERERERG9VxRFQb58+Yzej0ajQXR0NNzc3Ixu+c6OrD0/U2KLNREREREREZERsk1hvXjxYvj4+MDR0RHVq1fH6dOn37itWq3G//73P/j4+CBHjhwoWbIkZs+enYXREhEREREREb2ULQrrzZs3IyQkBBMnTsTZs2dRoUIFNGrUCI8fP05z++nTp2PVqlVYunQprly5gqlTp2LChAlYv359FkdORERERERE77tsUVjPnTsX/fv3R+/eveHr64tly5YhR44cWLt2bZrb//HHH2jdujUaN24MHx8fdOrUCR9++CFOnTqVtYETERERERHRe8/sk5clJSXhzJkzGD9+vG6ZjY0N6tevj5MnT6b5mJo1a+Kbb77BjRs3ULJkSfz111/466+/EBwc/NbniomJQUxMjO5+REQEgJeD8t/Xi8Rba94ajQZarZb5WSBrzg1gfpbOmvOz5twA5mfprDk/a84NYH6Wztrze5eMTNhm9sL68ePH0Gg08PT01Fvu6emJmzdvpvmYcePG4enTp/jggw9ga2sLEcHcuXPRrFmztz7X3LlzMXny5FTLnz17hpw5cxqeRCb735LjJt/n3XvRsLUBgmf8isyYPX/a4Fqm32kGaDQaxMbGQkSscgZDa87PmnMDmJ+ls+b8rDk3gPlZOmvOz5pzA5ifpbP2/N4lI9e4NnthbYgtW7bobqVLl8bp06cREhKCQoUKoXXr1m98XEhICPr27au7HxERgWrVqiF37txwc3PLitANEhXz7m0yKlkDKAAexgDaTCiszf16ajQaKIoCV1dXqzwIWHN+1pwbwPwsnTXnZ825AczP0llzftacG8D8LJ2152dKZi+s3d3doVKpEBUVpbc8KioKXl5eaT5m9OjRGD9+PNq3bw8AKF++PK5fv44ZM2a8tbB2cXGBi4tLquUqlSpbf1Ayo/CFAPL/950Z+88Or6eNjU22f2+NYc35WXNuAPOzdNacnzXnBjA/S2fN+VlzbgDzs3TWnp+pmH3yMnt7e/j7+2Pfvn26ZVqtFgcOHECNGjXSfEx8fHyqN1alUkGr1WZqrERERERERESvM3uLNfCyi3bPnj3h7++PatWqYf78+YiPj0evXr0AAD169IC3tzdCQ0MBAM2bN8eXX36JggULonTp0jh16hQWL16M0aNHmzELIiIiIiIieh9li8K6Y8eOePToESZMmIDIyEj4+flhz549usHi4eHhsLH5v8b1hQsXYvz48RgwYAAePnwIb29vjBw5EmPHjjVXCkRERERERPSeyhaFNQAEBQUhKCgozXWHDx/Wu+/s7IwFCxZgwYIFWRAZERERERER0ZuZfYw1ERERERERkSVjYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBFtzB0BZI/7aFr372oTH0CpA8tUtkFeWO5XqkLWBERERERERWTgW1u8pVQ532NkCyWpzR0JERERERGTZWFi/J15vibZRAE8XICoG0MobHkRERERERETvxDHWREREREREREZgizVZheDgYL37IgK1Wg1bW1soiqJbvnDhwqwOjYiIiIiIrBxbrMkqhYWFITw83NxhEBERERHRe4At1mQVXm+JDgoKglqtxoIFC6BSqcwUFRERERERvQ/YYk1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBBbWREREREREREZgYU1ERERERERkBIML6507d6Jp06bw9fXF3bt3AQDLly/Hvn37TBYcERERERERUXZnUGG9du1adO/eHRUqVEBYWBiSk5Nf7szGBjNnzjRpgERERERERETZmUGF9ezZs7Fq1SqEhobC1tZWt7x69eq4cOGCyYIjIiIiIiIiyu4MKqxv3bqFqlWrplru6OiI58+fGx0UERERERERkaUwqLAuUqQILl68mGr53r17Ubp0aaODIiIiIiIiIrIUtu/eJLWRI0diyJAhSEpKgojg7Nmz2Lp1K7766issXbrU1DESERERERERZVsGFdb9+vWDk5MTxo0bh/j4eHTo0AH58+fHrFmz0LVrV1PHSPTeCw4O1rsvIlCr1bC1tYWiKLrlCxcuzOrQiIiIiIjeewYV1gDQtWtXdO3aFfHx8YiNjYWHh4cp4yKitwgLC4OIoFixYuYOhYiIiIjovWdQYV2vXj38+OOPcHV1hZOTE5ycnAAAMTExaNWqFQ4ePGjSIIned6+3RAcFBUGtVmPBggVQqVRmioqIiIiIiAADJy87fPgwkpKSUi1/8eIFjh49anRQRERERERERJYiQy3Wly9f1v3/+vXrePz4se6+RqPBnj174O3tbbroiIiIiIiIiLK5DBXW5cqVg6IoUBQFgYGBEBG99Tly5ODkSURERERERPReyVBh/eqESadOnUK+fPl06+zt7eHh4cHxnkRERERERPReyVBhXaRIEQCAVqvNlGCIiIiIiIiILI3Bl9tKTk7G6dOnER4enmoisx49ehgdGBEREREREZElMKiwvnz5Mpo3b4779+8jOTkZOXLkQHx8PBwcHODs7MzCmoiIiIiIiN4bBl1ua9iwYahVqxaePXsGJycnXLx4EZcvX0blypWxZs0aU8dIRERERERElG0Z1GL9119/4fjx43BwcICNjQ2SkpJQunRpzJo1C3379kXTpk1NHScRERERERFRtmRQi7VKpYK9vT0AwNPTE+Hh4QCAvHnz4s6dOwYFsnjxYvj4+MDR0RHVq1fH6dOn37p9dHQ0Bg0aBE9PTzg6OqJMmTI4cuSIQc9NREREREREZCiDWqwrVaqE06dPo0SJEqhTpw4mTpyI6OhorF+/HuXLl8/w/jZv3oyQkBAsW7YMAQEBmD9/Pho1aoTr16/D3d091fZJSUlo0KABvLy88NNPP6FAgQK4ffs2PDw8DEmHiIiIiIiIyGAGtVh/9dVXuiJ22rRpyJ07N/r164fIyEisWLEiw/ubO3cu+vfvj969e8PX1xfLli1Djhw5sHbt2jS3X716NaKjo/HTTz+hZs2a8PHxQb169VCmTBlD0iEiIiIiIiIymEEt1sWLF4eLiwsAwMPDA3v27DE4gKSkJJw5cwbjx4/XLbOxsUH9+vVx8uTJNB+zY8cO1KhRA4MGDcLOnTvh4eGBPn36YPjw4VAU5Y3PFRMTg5iYGN39iIgIAIBGo4FGozE4h8xm8+aUjNpnyi0zZJfXM7vEkVmsMT+NRgOtVmuVuQHMz9JZc37WnBvA/CydNednzbkBzM/SWXt+76JSqdK9bYYLa41GAy8vL/z9998oVapURh+eyuPHj6HRaODp6am33NPTEzdv3kzzMbdv38aBAwfQs2dP/Prrr7h8+TKGDBkCGxsbDBs27I3PNXfuXEyePDnV8mfPniFnzpzGJZKJPF1Mv09FAVydAAEgYvr9R0dHp3vb/y05bvLnv3svGrY2QPCMX02e37TBtUy7QwOo1WpoNBpER0dn6A/eEmg0GsTGxkJErC43gPlZOmvOz5pzA5ifpbPm/Kw5N4D5WTprz+9d0hqW/CYZLqxVKhVKlCih1/Kb1bRaLby8vLB06VKoVCpUrlwZt2/fxrJly95aWIeEhKBv3766+xEREahWrRpy584NNze3rAjdIFGZ8FLbKIAC4GEMoM2Ewjojr2dm5Jesybz8ssNnxdb25Z+um5ub1R3kNBoNFEWBq6ur1eUGMD9LZ835WXNuAPOzdNacnzXnBjA/S2ft+ZmSQV3Bp0+fjlGjRmH58uUoXbq0UQG4u7tDpVIhKipKb3lUVBS8vLzSfIyXlxfs7e313twyZcroZid/ExcXF10X9lepVKps/UHJjMI3Zb8pN1PLyOuZKfnJy9b4zMgvO31Wsvtn11A2NjZWmxvA/CydNednzbkBzM/SWXN+1pwbwPwsnbXnZyoGTV7Wt29f/Pnnnyhbtixy5coFDw8PvVtG2Nvbw9/fH/v27dMt02q1OHDgAGrUqJHmY2rWrIlbt25Bq9Xqll2/fh2FCxc2JB0iIiIiIiIigxnUYj179myTBhESEoKePXvC398f1apVw/z58xEfH49evXoBAHr06AFvb2+EhoYCAAYNGoRFixZh5MiRGDRoEK5cuYI5c+akOX6aiIiIiIiIKDMZVFj37NnTpEF07NgRjx49woQJExAZGQk/Pz/s2bNHN1g8PDwcNjb/17hepEgR/PbbbxgxYgSWLl2KQoUK4fPPP8eQIUNMGhcRERERERHRuxhUWGeGoKAgBAUFpbnu8OHDqZbVqlULp06dyuSoiIiIiIiIiN7OoDHWRERERERERPQSC2siIiIiIiIiI7CwJiIiIiIiIjKCQYV1nz598Pz581TL4+Li0KdPH6ODIiIiIiIiIrIUBhXW69atQ0JCQqrlCQkJWL9+vdFBEREREREREVmKDM0KHh8fDxGBiCAhIQHx8fG6dRqNBnv37oWHh4fJgyQiIiIiIiLKrjJUWOfKlQuKokBRFBQrVizVekVRMHnyZJMFR0RERERERJTdZaiwPnToEEQE9erVw7Zt25AnTx7dOnt7exQpUgQFChQweZBERERERERE2VWGCuvAwEAAQFhYGAoXLgxFUTIlKCIiIiIiIiJLke7C+vLlyyhdujRsbGwQFxeHK1euvHFbX19fkwRHRERERERElN2lu7AuV64cIiMj4eHhgXLlykFRFIiIbn3KfUVRoNFoMiVYIiIiIiIiouwm3YV1WFgY8uXLp/s/EREREREREWWgsC5SpEia/yeiN2s+cnum7DfhTjTsbIE2Y3+BVt69fUbsnNPStDskIiIiIrJyGZq87FXXrl3DkSNH8PDhQ2i1Wr11EyZMMDowIiIiIiIiIktgUGG9ZMkSBAcHw8vLC/nz59ebHVxRFBbWRJRuwcHBevdFBGq1Gra2tnrHloULF2Z1aERERERE6WJQYR0aGopZs2YhJCTE1PEQ0XsuLCwMIoJixYqZOxQiIiIionQxqLCOjY1Fy5Ych0lExnu9JTooKAhqtRoLFiyASqUyU1REREREROlnY8iDevfujW3btpk6FiIiIiIiIiKLk+4W6zFjxujdDw0Nxd69e1G+fHnY2dnprZs5c6ZpoiMiIiIiIiLK5tJdWJ8+fVrvvp+fHzQaDc6fP6+3/NXJhoiIiIiIiIisXboL60OHDmVmHEREREREREQWyaAx1kRERERERET0EgtrIiIiIiIiIiOwsCYiIiIiIiIyAgtrIiIiIiIiIiOwsCYiIiIiIiIyQrpnBd+9e3e6d9qkSRODgiEiIiIiIiKyNOkurJs1a5au7RRFgUajMTggIiIiIiIiIkuS7sJaq9VmZhxERom/tkXvvjbhMbQKkHx1C+SV5U6lOmRtYEREREREZPXSXVgTWRJVDnfY2QLJanNHQkRERERE1s7gwvq///7Dnj17EB4ejqSkJL11EyZMMDowoox4vSXaRgE8XYCoGEArb3gQERERERGRCRhUWB8/fhzNmjWDq6sr7t27h2LFiuHevXuwtbVFqVKlWFgTERERERHRe8Ogy22NHj0affv2RVhYGBwdHfHrr7/i3r17qFmzJgYOHGjqGImIiIiIiIiyLYMK67///hsDBgwAANja2iIhIQFubm6YNm0avvzyS5MGSERERERERJSdGVRYOzk5ITk5GQDg5eWF27dvAwBUKhUePnxouuiIiIiIiIiIsjmDxlgHBATg+PHjKFOmDJo0aYJRo0bh8uXL2LZtGwICAkwdIxEREREREVG2ZVBhPWfOHDx//hwAMGXKFMTFxWHDhg0oWbIk5s6da9IAiYiIiIiIiLIzgwrrEiVK6P6fM2dOLFu2zGQBEREREREREVkSg8ZYFytWDE+ePEm1/OnTpyhWrJjRQRERERERERFZCoMK6zt37kCj0aRa/uLFC9y/f9/ooIiIiIiIiIgsRYa6gu/evVv3/wMHDiB37ty6+xqNBvv374ePj4/JgiMiIiIiIiLK7jJUWDdr1gwAoCgKunbtqrfOzs4OPj4+mDNnjumiIyIiIiIiIsrmMlRYa7VaAEDRokVx+vRpuLu7Z0pQRERERERERJbCoFnBw8LCTB0HERERERERkUUyqLAGgH379uHQoUN4+PChriU7xerVq40OjIiIiIiIiMgSGDQr+BdffIFPPvkER44cwdOnT/H8+XO9GxEREREREdH7wqAW6xUrVuC7775D586dTR0PERERERERkUUxuCt4lSpVTBkHEb1F/LUteve1CY+hVYDkq1sgryx3KtUhawMjIiIiIiLDuoIPHz4cS5cuNXUsRJROqhzucMjFWfmJiIiIiLIDg1qsz549i3379uGXX35B2bJlYWdnp7d+y5Ytb3gkERni9ZZoGwXwdAGiYgCtvOFBRERERESUJQwqrHPlyoXWrVubOhYiIiIiIiIii2NQYb1mzRpTx0FEFqj5yO0m32fCnWjY2QJtxv6SKa3xO+e0NP1OiYiIiOi9ZtAY6xR//fUXNm/ejLi4OABATEwMkpKSTBIYERERERERkSUwqMU6IiICLVq0wPnz56HVanHjxg0UK1YM48aNg0qlwsKFC00dJxEREREREVG2ZFCL9dChQ+Hj44Po6Gg4OTnplrdr1w579+41WXBERERERERE2Z1BLdaHDx/G77//jly5cuktL1asGO7evWuSwIiIiIiIiIgsgUEt1snJyWkuv3//fqpim4iIiIiIiMiaGdRi3bBhQyxcuBBLliwBACiKgri4OEyePBmNGzc2aYBERJYsODhY776IQK1Ww9bWFoqi6JZzbgoiIiIiy2VQi/XcuXNx5MgRVKhQAYmJiejRoweKFSuGO3fuYMaMGQYFsnjxYvj4+MDR0RHVq1fH6dOn0/W4GTNmQFEUjBo1yqDnJSLKSmFhYQgPDzd3GERERERkQga1WBcsWBAXLlzApk2bcPHiRcTGxqJHjx7o2rWr3mRm6bV582aEhIRg2bJlCAgIwPz589GoUSNcv34d7u7ub3zc2bNnsWzZMlSoUMGQNIiIMt3rLdFBQUFQq9VYsGABVCqVmaIiIiIiIlMyqLAGAFtbW3Tr1s0kQcydOxf9+/dH7969AQDLli3Drl27sHbt2je2RMfHx6Nbt25YtmwZQkNDTRIHERERERERUUYZXFjfvXsXR48excOHD6HVavXWhYSEpHs/SUlJOHPmDMaPH69bZmNjg/r16+PkyZNvfNzIkSNRt25dNGrUKN2FdUxMDGJiYnT3IyIiAAAajQYajSbdMWc1G+Xd2xiyz5RbZsjI62lp+Zk7t5T9Wm1+CqBk1r6RsfwyU3aJw9Q0Gg20Wi3zs0DWnBvA/CydNednzbkBzM/SWXt+75KR3oUGFdarVq3C4MGD4eTkBHd3d70JeBRFyVBh/fjxY2g0Gnh6euot9/T0xM2bN9N8zC+//IKDBw/i3LlzGYp77ty5mDx5cqrlz549Q86cOTO0r6zk6WL6fSoK4OoECAAR0+8/Ojo63dtaWn7mzg2w7vzuqgCVDeDhYv7PZmZQq9XQaDSIjo62yq7gGo0GsbGxEBHmZ2GsOTeA+Vk6a87PmnMDmJ+ls/b83uVtw5JfZ1BhPWnSJEydOhVjxozRK6qzwqNHj9C/f3/8/PPPGR7PHRISgr59++ruR0REoFq1asidOzfc3NxMHarJRMW8e5uMsvn/rYIPYwBtJhQvGXk9LS0/c+cGWHd+yZrs89nMDLa2tro4rPELSqPRQFEUuLq6Mj8LY825AczP0llzftacG8D8LJ2152dKBhXWL168QLt27UxSVLu7u0OlUiEqKkpveVRUFLy8vFJt/88//yAiIgI1a9bULdNoNPj999+xaNEiJCYmvvG5XFxc4OKSuolNpVJl6w9KZhQXKftNuZlaRl5PS8svO+SWsm+rzE9etsRnh89mZsruxx1j2NjYMD8LZc25AczP0llzftacG8D8LJ2152cqBl1ua+DAgVi/fr1JArC3t4e/vz/27dunW6bVanHgwAHUqFEj1fZVq1bFpUuXcP78ed2tSpUq6NmzJ86cOWOSmIiIiIiIiIjSy6AW68mTJ6NJkyaoXLkyypYtCzs7O731q1evztD+QkJC0LNnT/j7+6NatWqYP38+4uPj0atXLwBAjx494O3tjdDQUOTMmRPlypXTe3zOnDmRN29elC1b1pB0iIiIiIiIiAxmUGE9duxYHDhwANWrV0dCQsJbu1+nR8eOHfHo0SNMmDABkZGR8PPzw549e3SDxcPDw2FjY1DjOhERkcGCg4P17osI1Go1bG1t9YZDvX69ciIiInq/GFRYL1++HFu2bEHr1q1NFkhQUBCCgoLSXHf48OG3PvZd64mIiEwhLCwMIoJixYqZOxQiIiLKRgwqrHPnzo0yZcqYOhYiIqJs5fWW6KCgIKjVaixYsICTuBAREZGOQf2rv/jiC0yZMsXoLuBEREREREREls6gFuuVK1fi2rVr8PT0RLFixVJNXnbq1CmTBEdERERERESU3RlUWDdr1gzNmjUzdSxEREREREREFsegwnrixImmjoOIiIiIiIjIIvEaVkRERERERERGSHeLtYeHBy5fvgx3d3fky5dP7/qdr3v48KFJgiMiIiIiIiLK7tJdWM+aNQvOzs4AgNmzZ2daQEREZDmCg4P17osI1Go1bG1t9U7Avn7ZKiIiIiJrku7CumfPngAAtVqNXLlyoU6dOsiXL1+mBUZERJYnLCwMIoJixYqZOxQiIiKiLJPhyctsbW3RrVs3XL16NTPiISIiC/J6S3RQUBDUajUWLFgAlUplpqiIiIiIspZBk5dVrVoVFy9eNHUsRERERERERBbHoMttBQcHIyQkBPfv34e/vz9y5sypt97X19ckwRERERERERFldwYV1h07dgQADB48WLdMURSICBRFgUajMU10RERERERERNmcQYV1WFiYqeMgIiIiIiIiskgGFdZFihQxdRxE9J6Kv7ZF77424TG0CpB8dQvkleVOpTpkbWBEREREROlk0ORlALBz5040bdoUvr6+uHv3LgBg+fLl2Ldvn8mCI6L3jyqHOxxyuZs7DCIiIiKidDOoxXrt2rUYPnw4Bg0ahIMHDyI5ORkAYGNjg5kzZ6JBgwYmDZKIrNfrLdE2CuDpAkTFAFp5w4OIiIiIiLIRg1qsZ8+ejVWrViE0NBS2tv9Xm1evXh0XLlwwWXBERERERERE2Z1BhfWtW7dQtWrVVMsdHR3x/Plzo4MiIiIiIiIishQGFdZFihTBxYsXUy3fu3cvSpcubXRQRERERERERJbCoDHWI0eOxJAhQ5CUlAQRwdmzZ7F161Z89dVXWLp0qaljJCIiIhMLDg7Wuy8iUKvVsLW1haIouuULFy7M6tCIiIgsjkGFdb9+/eDk5IRx48YhPj4eHTp0QP78+TFr1ix07drV1DESERFRJgsLC4OIoFixYuYOhYiIyOIYVFgDQNeuXdG1a1fEx8cjNjYWHh4epoyLiIiIMtHrLdFBQUFQq9VYsGABVCqVmaIiIiKyTAYX1gBw8+ZNXLlyBQDg6+uL4sWLmyQoIiIiIiIiIkthUGH96NEj9OnTB7t27YK9vT0AIDk5GY0bN8bq1avZek1EVqH5yO0m32fCnWjY2QJtxv6SKdfp3jmnpel3SkRERERvZVBh3adPH9y7dw+nT5+Gv78/AODMmTPo378/+vbtix07dpg0SCIiIqKM4ORsRESUlQwqrA8cOIDff/9dV1QDgL+/P5YtW4bAwECTBUdERERkCpycjYiIMpNBhbW3t7fe2d4UiqLAy8vL6KCIiIiIjMHJ2YiIKCvZGPKgGTNmYOjQobh48aJu2YULFzBixAjMmjXLZMERERERERERZXcGtVgPGDAAz58/R6VKleDg4AAAePHiBezs7DBo0CAMGjRIt+3Dhw9NEykRERERERFRNmRQYT179mxTx0FERERERERkkQwqrHv27GnqOIiIiIiIiIgskkFjrOfPn5/m8sTERAQFBRkTDxEREREREZFFMaiwDg0NRcOGDfHgwQPdsr/++gt+fn44cuSIyYIjIiIiIiIiyu4MKqwvXrwIW1tblC9fHps2bcKUKVNQq1YtNG7cGH/99ZepYyQiIiIiIiLKtgwaY+3p6Yndu3djzJgx6NKlC2xtbbFjxw588sknpo6PiIiIiIiIKFszqMUaAFauXImlS5eidevWKFSoEMaNG4d//vnHlLERERERERERZXsGtVg3b94cx48fx7Jly9C1a1fExsZi6NChqFq1Kr788kuEhISYOs5MFdHjf1By5NLdzxFYBXnG9Hm5rvtn0P73TG97+/IlkW/6CADAw6GhSL51V2+9rbcHPFdMAgA8nrQYL07rn3BQnBxRYOtcAED0gu8Qv/dEqpjy/zAPNjkcELN+B4b++n2q9evqNMOznM6o8O91fHT5TKr1W6vXR4RbPhSPvIum546lWr+nUi08dykMr+hHaHdyf6r1R8pUxgWfUnCJj0WvIztTrf+rWBmcKOUHlUaDIXu3pFof7f0MbiE9AAAPOo6CxMbrrXeoXAbuU4MBAN2O7kKe2Bi99Y+dc2Nj7SYAgNanD6LQ4yi99Qn2Dlj5cRsAQKMLJ1Dqwb/6ASjAD+07ArBB7avnUDnsaqoYV3/UArE5cqJS2FV8ePVcqvWbazRElGtefPDgDj65cFK3/P7V3wAAeb4YiBzVK+DFxet4/Nn8VI93Der88t/YGPQ4uivV+j9LlMOfJcvDPjkJA/dvS7X+70LFcbBcNQDAoL1bYKfR6OX3sGABbCkfCADoeWQncsfH6j0+KncebK7ZCADQ/o99yB/9WG99rGMOrK7bCgDQ+NwxlIy8q5cfVDbw3rEIAPB02RbE7TycKsYcRQOR4OCIKrf+Qc3rF1Ot31jrEzx2cUOZe7fR4NKfqdZvr/IR/s2XH0UeRaDlX4d1udmrgCQNsK9cAK4ULAb3mGh0Ob4n1eNPfFABfxUvixwvEtHv4E+p1l8o8gGO+PoDAIJ+2wQbrfxffgBy1K6MPJ/1BQBE9vwfNI+f6j2+/VMbbK3eAADQ8cRv8Hz2n976Z065sC6wOQCg+ZkjKPrwgd76ZJUKSxt2AADU+/sUyt29BW3CYygKoNz4HhBgWf22SLKzR8CNSwi4+XeqHNZ/2BRPc7mgXPhN1PvndKr126rVw/28nigadQ/Nzx7Vyw8A3Eb3htNHVZF0/Q4ejZiZ6vEufdvAuXV9qB9FI6rX56nW52pTH7k/bQNRq/Gg5dBU63PUrYo8o3oDACK6jEGHczcgAkS0CIICBQ5+peH+1cvHRQ35Cuo79/Ueb1vYC55LJwAAHn+xEC/OXtFbr+RyQoHNLy/xGD13PeIP/JEqhgI/LYBib4dna39G7Na9qdZ7fjMFtl7uiN1+CM9WbE213n32KDiUKYb4o2cQPf2bVOvz/K8fctSqhBf/3ESHA/r5AUDuQR2Rq1kg1A8eIqrfpFSPd+74CVx6tIA24QUi2o1Itd6pYU24DesGAHjQPgQSn6i33qFqWbhPGgIAiOo/Cer7D/XW2xUvBI+vPwMAPBo3D0mXbuitt8mTG/m/DQUA/DdzNRKOpB6y5b1rCQCg0s0nerml8Fo/Daq8rni+bR9iVqf+W8u3YBzsSxRG/ME/ET1nXar1eScOgmO18kg8dwVPxi9Mtd51aFfkbFQLyf8+wMPBX6Za79y9OVw6NYb2eRwiOo1OtT5n0zpwHdwJAHC/1VAgWa233rFGRd3/H346AdpH0Xrr7UsXRb45L/f7aOQsJF0N01uv8sgDrzUv43ry5XIknrygH4CdLbx//hoA8HTJJsTt+j1VjPk3zYKNc07EbPoVz79N/b3qsWQ87IoUQNxvx/H06w2p1uf9MhiOlcog8dQlPJm8NNX63CO6A34lkXwzHJEhs1Ktd+nTGs5tG0Dz5Ckie/wv1fpcreohd792AID7TQenWm/u30YCgcPy8QCAmPU78Hxz6u8Ez5WTYFvAA7G/HMGzpZtTrXefGQKHsiWQcPwc/pu2MtV6t3GfwulDf7y4chuPR6W+tGzu/u2Rq2VdqCMfI+rTCanW52rfELl7tYIkJeNB62Gp1jt9XD3N30YCgVqthlQtj3xf/v/j5aApUIdH6j3e1scbnotfHqcff/41XpzX/21jkzsX8m98eZz/b/YaJBxK/Z1RYPvXUGxt8eybHxH7Y+rff55rv4JtPjc8/2k/Ylb9mGp9vnljYP+BD+IPn0b0rDWp1qf12yglv0RbW7gFdUHOxh8i+V4UHg6YnOrxzl2awqVrU2jjEhDRYWSq9U6f1IJbcFcAwIO2wyGJSXrrHQPKI++EQQCAyL4ToYl4pLfermRheMwfBwB4NHo2ki7f1luvcneF17ppAID/Qlch4dhZ/QDS+G30an4KFHhtmAGVqzOeb9mDmHU7UuXgsfB/sCtWEHH7TuLp/G9Trc87ZQgc/csi8cw/eDJhcar1rsO7I2eDGki+fQ8Pg6elWu/SswWcO3wCzdPniOw6NtX6nM0/guvAl79N7rcIAjRavfWv/zZSP47Wy8/etxjyzRoFAHg4fDqSb4Trv0T588Fr1cv39smUpUj885LeesXRHgW2zQcARC/cgPg9x1PFmH/LHNjkzIGYDbvwfGPq39AeyyfCrqAn4n49iqeLUtdJ7qHD4VDhAyT8cRH/TV2Wan1GfhvZ5nNLtf5NDGqxjo2NxYULF9C168sPdq5cubB69Wps3LgR06dPN2SXRERERERERBZJERHJ6INEBIqipLnu4cOH8PDwMDqwrHDv3j0UKlQId+/eRcGCBc0dzhs1H7nd5Pu0UQBPFyAqBtBm+BPwbjvntEz3tpaWn7lzA6w7P2v/bCZc2wI7W8C+RAez55cZgoKCoFarsXjxYqhUKrPGkhmsOT9rzg2w/vw0Gg2io6Ph5ubG/CyMNecGMD9LZ+35mZJBLdaKouDChQsICgpC48aNERERAQDYtm0bwsPD3/FoIiIiIiIiIuthUGG9e/duVK9eHU+ePMGhQ4eQkJAAALh79y6mTJli0gCJiIiIiIiIsjODJi+bMGECFi5ciL59+8LZ2Vm3vE6dOpgxY4bJgiMiosyTKV3d70TDzhZoM/YXsw5TICIiIspKBhXWV65cQf369VMtd3V1RXR0dBqPICIiyjqZNb8BTxwQERFRWgzqCu7h4YHbt2+nWn7ixAkULVrU6KCIiIiIiIiILIVBhXW/fv0wbNgwnDlzBoqiICoqCps3b8aoUaMwYMAAU8dIRERERERElG0Z1BX8s88+g4ggMDAQ8fHxqFWrFuzt7TFixAgMHz7cxCESERERERERZV8GFdaKouDzzz/H6NGjcfPmTcTGxsLX1xe5cuUydXxERERERERE2ZpBhXUKe3t7+Pr6mioWIiIiIiIiIotj0BhrIiIiIiIiInqJhTURERERERGREVhYExERERERERmBhTURERERERGREYyavIyIiN4u/toWvfvahMfQKkDy1S2QV5Y7leqQtYERERERkcmwsCYiykKqHO6wswWS1eaOhIiIiIhMhYU1EVEmer0l2kYBPF2AqBhAK294ENE7NB+53eT7TLgTDTtboM3YXzLls7lzTkvT75SIiCib4BhrIiIiIiIiIiOwsCYiIiIiIiIyQrbpCr548WLMmjULkZGR8PPzw8KFC1G1atU0t125ciXWr1+Pv//+G4qioEqVKpg2bRqqVKmSxVETERGRqbGrOxERWZps0WK9efNmhISEYOLEiTh79iwqVKiARo0a4fHjx2luf/jwYXTu3BmHDh3CiRMn4O3tjQYNGiAiIiKLIyciIiIiIqL3XbYorOfOnYv+/fujd+/e8PX1xbJly5AjRw6sXbs2ze03bNiAwYMHw8/PD6VLl8aqVaug0Whw6NChrA2ciIiIiIiI3ntm7wqelJSEM2fOYPz48bplNjY2qF+/Pk6ePJmufcTHxyM5ORl58uR563YxMTGIiYnR3U9p4dZoNNBoNAZEnzVslMzZZ8otM2Tk9bS0/MydW8p+rTU/fjaNY+78oABKJu3b7LkB1p1fJuYGML/MptFooNVqzR5HZrHm/Kw5N4D5WTprz+9dVCpVurc1e2H9+PFjaDQaeHp66i339PTEzZs307WPcePGoVChQqhXr95bt5s7dy4mT56cavmzZ8+QM2fO9AedxTxdTL9PRQFcnQABIJkw1iw6Ojrd21pafubODbDu/PjZNI6587urAlQ2gIeL9X02AevOLzNzA5hfZtNoNIiNjYWIZOiHoKWw5vysOTeA+Vk6a8/vXdzd3dO9rdkLa2PNnDkTmzZtwpEjR2Bvb//WbUNCQtC3b1/d/YiICFSrVg25c+eGm5tbZodqsKiYd2+TUTb//8z9w0y6lm5GXk9Ly8/cuQHWnR8/m8Yxd37JGuv9bALWnV9m5gYwv8ym0WigKApcXV2t8sevNednzbkBzM/SWXt+pmT2wtrd3R0qlQpRUVF6y6OiouDl5fXWx86ePRvTpk3D/v37Ua5cuXc+l4uLC1xcUp8GV6lU2fqDkhk/AFL2m3IztYy8npaWX3bILWXf1pofP5uGM3t+8rI13lo/m1adXybmBjA/UwsODta7LyJQq9WwtbWFovxff/eFCxdmaVymYu35vc7Gxibb/x41BvOzbNaen6mYffIye3t7+Pv7Y9++fbplWq0WBw4cQI0aNd74uJkzZ2Lq1KnYs2cPL7NFRERE77WwsDCEh4ebO4xMY+35EZHlM3uLNfCyi3bPnj3h7++PatWqYf78+YiPj0evXr0AAD169IC3tzdCQ0MBADNmzMCECROwceNG+Pj4IDIyEgCQK1cu5MqVy1xpEBEREWWJ11tqg4KCoFarsWDBAqtoVbL2/IjI+mSLwrpjx4549OgRJkyYgMjISPj5+WHPnj26weLh4eGwsfm/xvWlS5ciKSkJ7dq109vPxIkTMWnSpKwMnYiIiIiIiN5z2aKwBl6eiQwKCkpz3eHDh/Xu37lzJ/MDIiIiIiIiIkqHbFNYExGR5Ym/tkXvvjbhMbQKkHx1C16dH8qpVIesDYyIiIgoC7GwJiIik1HlcIedLZCsNnckRERERFmHhTURERns9ZZoGwXwdHl5HeLMvNwcERERUXZi9sttEREREREREVkytlgTERERERGlQ3BwsN59EYFarYatrS0URdEtf/2ScWT92GJNRERERERkgLCwMISHh5s7DMoG2GJNRERERESUDq+3RAcFBUGtVmPBggVQqVRmioqyAxbWREREb8DLiREREVF6sLAmIiJKJ15OjIiIiNLCwpqIiOgNeDkxIiIiSg8W1kRERO8hdnMnIiIyHRbWRERExG7uRERERmBhTURE9B5iN3ciIiLTYWFNREREVodd3YmIKCuxsCYiIiKrx67uRESUmVhYExERkdVhV3fKroKDg/XuiwjUajVsbW2hKIpu+cKFC7M6NCIygo25AyAiIiIiel+FhYUhPDzc3GEQkZHYYk1ERERElEVeb4kOCgqCWq3GggULoFKpzBQVERmLLdZERERERERERmBhTURERERERGQEFtZERERERERERmBhTURERERERGQEFtZERERERERERmBhTURERERERGQEXm6LiIiIKAs1H7nd5PtMuBMNO1ugzdhfoBXT7nvnnJbp3jYzcgOyT35ERG/CFmsiIiIiIiIiI7CwJiIiIiIiIjICC2siIiIiIiIiI7CwJiIiIiIiIjICJy8jIiIiIiKTCA4O1rsvIlCr1bC1tYWiKLrlCxcuzOrQiDIVW6yJiIiIiChThIWFITw83NxhEGU6tlgTEREREZFJvN4SHRQUBLVajQULFkClUpkpKqLMxxZrIiIiIiIiIiOwsCYiIiIiIiIyAgtrIiIiIiIiIiNwjDURERERUTo0H7nd5PtMuBMNO1ugzdhfoBWT7x4757Q0/U6JKBW2WBMREREREREZgYU1ERERERERkRFYWBMREREREREZgYU1ERERERERkRE4eRkRERGRhYm/tkXvvjbhMbQKkHx1C16d/8qpVIesDcxErD0/IrI+LKyJiIiILJwqhzvsbIFktbkjyRzWnh8RWT4W1kREREQW5vWWWhsF8HQBomKQKZdsymrWnh8RWR+OsSYiIiIiIiIyAgtrIiIiIiIiIiOwKzgRERERURbhxGxE1omFNRERERGRmXBiNiLrwMKaiIiIiCiLcGI2ys6Cg4P17osI1Go1bG1toSiKbvnChQuzOrRsj2OsiYiIiIiIKJWwsDCEh4ebOwyLwBZrIiIiIiIiStUSHRQUBLVajQULFkClUpkpKsvAFmsiIiIiIiIiI7DFmoiIiIiI0HzkdpPvM+FONOxsgTZjf8mUMeQ757RM97aWll9GciPzY4s1ERERERERkRFYWBMREREREREZgYU1ERERERERkRFYWBMREREREREZgYU1ERERERERkRE4KzgREREREZlE/LUteve1CY+hVYDkq1vw6qTZTqU6ZG1gRJks27RYL168GD4+PnB0dET16tVx+vTpt26/detWlC5dGo6Ojihfvjz27NmTRZESEREREVF6qHK4wyGXu7nDIMp02aLFevPmzQgJCcGyZcsQEBCA+fPno1GjRrh+/Trc3VP/IZ44cQKdO3dGaGgomjVrho0bN6Jly5Y4f/48ypQpY4YMiIiIiIjo9ZZoGwXwdAGiYpAp17HOamyRpzfJFi3Wc+fORf/+/dG7d2/4+vpi2bJlyJEjB9auXZvm9gsWLEDjxo0xevRolClTBlOnTkWlSpWwePHirA2ciIiIiIjeW2yRpxRmb7FOSkrCmTNnMH78eN0yGxsb1K9fHydPnkzzMSdPnsTo0aP1ljVq1Ai//PLLW58rJiYGMTExuvt3794FANy7dw8ajcbQFDLdi9jHJt+njQLEA3gRmzlnD//99990b2tp+Zk7N8C68+Nn0zjWnJ+5cwOsOz9+No1jzfmZOzfAuvPjZ9M4WZ2fyrue3n0bBcibC3j8Wn6meK6M5GYqEydO1LsfHh4OEcGnn36qt3zy5MlZGZbZqFQqeHl5wdY2HWWzmNn9+/cFgPz55596y0ePHi01a9ZM8zF2dnayefNmvWWLFy+WAgUKvPW5Jk6cKAB444033njjjTfeeOONN9544+2dt7t376arrjV7i3VWCgkJQd++fXX3ExMTcffuXRQtWjR9ZyGsSEREBKpVq4ZTp04hf/785g7H5Jif5bLm3ADmZ+msOT9rzg1gfpbOmvOz5twA5mfprD2/9PDy8krXdmavJt3d3aFSqRAVFaW3PCoq6o1JeHl5ZWj7FC4uLnBxcdFbVqJECQOith758+dHwYIFzR1GpmF+lsuacwOYn6Wz5vysOTeA+Vk6a87PmnMDmJ+ls/b8TMHsk5fZ29vD398f+/bt0y3TarU4cOAAatSokeZjatSoobc9AOzbt++N2xMRERERERFlFrO3WAMvu2j37NkT/v7+qFatGubPn4/4+Hj06tULANCjRw94e3sjNDQUADBs2DAEBgZizpw5aNq0KTZt2oQzZ87gm2++MWMWRERERERE9D7KFoV1x44d8ejRI0yYMAGRkZHw8/PDnj17dNewDg8Ph43N/zWu16xZExs3bsT48ePxv//9DyVLlsTPP//Ma1hngIuLCyZOnJiqa7y1YH6Wy5pzA5ifpbPm/Kw5N4D5WTprzs+acwOYn6Wz9vxMSRERMXcQRERERERERJbK7GOsiYiIiIiIiCwZC2siIiIiIiIiI7CwJiIiIiIiIjICC2siIiIiIiIiI7CwJiIiIiIiIjICC2siIiIiIiIiI7CwJiIiygZ49UvKLPxsERFlPhbW9EZxcXG6/1vbl7K15UNElikuLg4XL14EACiKAq1Wa+aIXko5RmaXeCjjnj17BgBQq9VQFAUAv/sswfv8N6fRaMwdQpZ63/J9HyjCoyy95rvvvsOhQ4fw8OFD1KlTB6NHjzZ3SJlKo9FApVJBRHQ/Pih70mq1sLGxzvOBKZ9Den8sXboUW7duxR9//IGyZcti9+7dyJcvn1liSfnbunHjBuLi4uDp6Qk3Nzc4Ojqm2sbaj5UXLlzAqVOnUKdOHZQqVQoALCrne/fuYcaMGdi1axeKFSuG4sWLo2fPnqhZsyYA6zyOighExKry+umnn/Dbb7/BxcUFFSpUQOPGjZE3b15zh5UpXv1Mvg/fhUeOHIGtrS1q1aoFwHL+JqOionDhwgUcP34cbdu2RYUKFQBY1vExs2X/d5Gy1KJFizB16lTExsaicOHCWLNmDebPnw/AOs6ixsXFYejQofj1119x7tw5xMfH6w7gr7YWWUOur7KW82c2NjZWd4b3zJkzAACVSmV1uaUl5Qfw++7PP//EZ599hhYtWmDHjh0AgNWrV5stnpQfdQEBAahRowa++OILNG7cGPPnz8f+/ftx//593TaKoljde5jyt7dy5Up8/vnnOHPmDLy8vAD8349GS/nstmjRAhEREZg4cSKqVKmCvXv3omnTphg/fjwAWMQP+PQIDw/H77//jgsXLkBRFNjY2Fj8d3fK53DNmjUYMmQInj9/jqtXr+LLL7/E6NGjcfToUTNHmDlatmyJ9u3bIy4uTvebzNLfyzcREWzYsAEffvghJk6cCAAW89nt2LEjgoODsWLFCvj7+2Pq1KkAwKL6VUL0/4WHh4urq6ts27ZNRETi4+Nl5MiRUqVKFVGr1WaOzjSGDBkiiqJI6dKlpV27dlKsWDEZO3asLF26VK5duyZarVY0Go25wzRIStw3btyQ77//Xnbt2iWnTp3SrddqteYKzWgHDhyQMWPGSEJCgm6ZJeeTYuXKlWJrayvDhw+XmJgY3XJL/Qy+zZIlS+TGjRu6+9aYY0bUqVNHPvvsM939mTNnSvfu3aVHjx7SuHFj2bJli7x48SLL4kn5e+rXr5907txZNm3aJEuWLBE/Pz/p3LmzeHh4yODBg+XLL7+U48ePS2RkpNW8hyl5nD17VvLmzSs//vijREREiIjI3r17pXr16nL06NFU22dH3377rVSoUEHvWPnFF19IoUKFpGLFijJgwACJjo42X4Am8u2330q1atXEx8dH8uTJI+PGjTN3SCYTFRUlHh4esm7dOhERWbVqleTIkUOqVKkiAQEBsmrVKnn+/LmZozQNrVYrYWFhYmtrK4UKFZKiRYvKzp07desTExPNGF3mefTokSxZskTy5MkjlSpVknv37unWZdffNh07dpQPP/xQrl69Kk+fPpXly5eLoiiyY8cOc4eWrbCwJp0vvvhCWrRoIUlJSbo/7IcPH0qxYsXk4sWLZo7ONP7++28ZPny47N+/X+7duyfffvut9OnTR+rVqycqlUratWsnn376qSxbtkwePXpk7nDTLeXEx/nz5+WDDz6QMmXKSOnSpSUwMFC+/PJLizhov0lsbKx4eXlJ3rx5pVGjRnLs2DHdOks+4RMRESElSpSQRo0aSe3atSUwMFD279+vW/96bpb2vr1qypQpoiiKtGzZUn788Ufd8uxcoGSm2NhYadCggXzzzTe6ZYGBgVK2bFkZM2aMtG/fXhwdHWXz5s1ZHtuRI0ekdevWeoXk6dOnRVEUqVWrljRr1kwURZEGDRpY9GcyLRUqVJARI0bo7sfHx0v+/PmldOnSUqRIEZk0aZIZo0ufpUuXSvXq1eXZs2e69+fXX3+VevXqydSpU6Vw4cKyd+9eM0dpnBs3boiTk5N88803cvjwYQkJCZEcOXLIb7/9Zu7QDPbPP//IlStXRERkzpw50qRJExF5mWvevHll+/btcvbsWcmXL58ULVpUhg8fbtHff69r0KCBjB8/XkJCQsTV1VWGDh0qIiITJ06US5cuWd2xRkQkISFBbt++LXny5BFHR0dZsmSJbl12e2+3bNkiuXLl0v0u1mg08vTpU6lYsaIsXrzYzNFlLyysSURe/mhftWqVjBgxQvcHnZSUJC9evBBfX1/5/vvvddsOHDhQjhw5Yq5QjRIfHy+9e/eWgIAAiYqK0i0vWbKktGnTRsaMGSOdO3cWBwcHuX37thkjNYyvr68EBQWJiMiOHTtEURSpUKGCdOrUSX7//XczR2eYSZMmSZ06dWTRokXStm1bKVeunISGhurWa7VavS9dS/kCXrp0qXz88cfyxx9/yI4dO6RDhw5StmxZmTx5sl4O8fHxZozSeNevX5dy5cpJ3759pX379lKrVi354osv5OHDh7ptXs33fSi2X7x4IXXr1hVfX1/54YcfZNCgQZInTx69E2CdOnWSevXqmeX1mDhxori7u+uOGU2aNJEmTZqIWq2WJ0+eSFhYmPzzzz9ZHldm+uWXXyQgIECuXbumWzZw4EBp3ry5XL16VaZPny6+vr5Ss2bNbN3iu3v3bilRooQcPnxY/vvvPxERKVOmjIwfP15ERNq2bSuNGjVKddy0JGXKlJGRI0fq7h89elQURZHPPvtMLl++LLt375bY2Fh58OCBGaPMmHz58snChQtF5GUxnXJSrV+/ftKtWzdJSkoSEZFWrVpJ69at5cSJE2aLNTOsXLlSgoODJS4uThYvXixly5YVd3d3cXJy0m2TnJxsxghNR61W697P33//Xdzc3KRXr17i6Ogon3zyicTGxopI9vkto1arpXr16pI7d255+vSp3joXFxeznADOzlhYk+5gFRkZqfsievXHXOPGjWX06NEiIrJx40ZRFEXu3r2b9YGaUPv27WXw4MEi8rKl3tvbW68r7rNnz8wVmsFWrlwpVatW1d0vW7asjBs3TlasWCE5c+aUatWqyVdffZXtzoS+TVJSkkyePFlGjRolGo1GLl68KGPHjhU/Pz9p06aN7gy/iMjPP/9sxkgz7tGjR7Js2TLd/YsXL8oXX3whlStXlmbNmsn58+dF5OWZ/AULFpgrTKNt375d6tWrJ5cvX5bbt2/LqFGjpFatWtKhQwc5ePCgbrs7d+7oCoH3wb1796Rx48ZSrlw56dy5s3Tp0kVERPejaubMmdKwYUOzdfkcOnSozJkzR2bNmiWurq5y6dIlvfXZ5UefsVLy+Omnn8THx0fXBVzkZbGdcgIoISFBZsyYIRUrVtQ7KZvdPH/+XJo2bSpeXl5Sq1YtKVOmjFSoUEH3Q37KlCnSuHFjEbHM9zCl++kff/yhW9a9e3dxcnKStm3bSt26daVgwYJSvHhxcXV1lcmTJ5sx2vTp2LGjVK9eXW9Zym+QNm3ayJAhQ3TL27Zta1Vdb1M+g6dPn5bixYvLzZs3ReTl0CE7OztxdnaWWbNmmTNEk/npp5/0Tg5oNBrx8fGRyZMni0ajkd9++038/PzEzc1NNm3aZMZI9SUnJ8uxY8ekXr16kiNHDlmxYoWIvDzpU6NGDTNHl/2wsCYZP368nDx58o0tI1OmTJE2bdpIfHy8uLi4yMqVK7M4QtNJKSpTWiemTZsmDg4Oel9UlvRj49VYjxw5ItOnTxcRkQkTJkjNmjV14+zq168vlSpVkrVr15olTmOFh4fr/v/kyRNZs2aNNGrUSPz8/GTt2rXy888/i6Ioeq1N2dXdu3dTtaSkvI9Pnz6Vb7/9Vpo1ayb+/v7Spk0bUalUFn8i69y5c7r/JyUlyZo1a6RJkyYSGBgoc+bMkYcPH0r16tVl0KBB5gsyC73eI+G7776TKlWq6Ja9ePFCatasKWPGjMn0WFKO+xqNRu7fv69bvm/fPsmTJ48oiiIbN27M9DjMbevWreLl5ZXmiYyU9+uXX36ROnXq6B2PsoO0vruXL1+umz/k1WFNn3/+ua7F2hJ9//330rhxY9332Q8//CAeHh5y+PBhEXl5DH3x4oXs3LlTNm7cKE+ePDFzxG+3ZcsWcXJy0uutsnnzZl1h9b///U9q164tU6dOlSFDhoibm5vVtNy+rmfPnrJr1y4RESlSpIj07NlTZs6cKa6urtKkSROL7s20a9cuKVmypAwePFjX26dHjx7y4Ycf6k56abVauXXrlnTr1k0++eQTc4ari+fV/0dGRsrEiRNFpVLpTgCkfG4tqcEms7Gwfs8NHz5cFEURf39/WbdunV4Xt1fP5AcEBEjVqlWlQYMGZorU9CZNmiSKokj37t3NHYpJvHjxQvcjokOHDrqufyIvuzRu2LDBXKEZ7PUv0lcP9MeOHZOgoCApU6aMKIoiU6dOzerwDPLhhx+m2br+am6nTp2Srl27iqIoFvm+ibzs4rZ161a9Za/+IDx9+rQMHDhQ6tSpIyVLlpR8+fJl6WRd5vbqD5GHDx9KhQoVdBOaNW/eXMqXL59pz53yWXv176t3796pekZs27ZN/Pz8ZPv27alitjZPnjyRYsWKSbdu3dLsQpyYmCg1atTQjf3MTlLezwULFuhak14XGxsru3fvFicnJ/n111+zMjyTSTnxc+rUKQkJCZHy5cuLoih6rdIpRYoliI2NlVy5cumdQLt69aooiiK//PKLiLzsydShQwfx8/OTGjVqWOwwvNelNXxryZIl8umnn0qbNm2kXLlyEh8fLzExMfLjjz/qTpxYqkePHslXX30lH3/8sbRu3VqGDBkiefPm1Z2ke/VY/Pz582zxXahWqyUxMVHvxH5iYqLs27dP6tevLw4ODnrzNVjyiQ9TYmH9nvvxxx+lRIkSUrJkSVEURXr27ClXr15N9SNfURRxd3e3qC8tkbQP3inUarV06tRJevXq9cZtsqvo6Gj58ccfZcaMGWm2JgUFBcmHH34oe/fulW3btomDg4Ncv37dDJGa3qvv0e3bt6Vo0aIWccInJe5mzZpJhw4dROTNJw60Wq1UqFBB2rVrl7VBmsjTp0/F0dFRd4WBV736/sXFxcmgQYNEURS9buHW6NWiNOX/sbGx8sMPP4jIyyK2W7duUrx4cRk9erSuS2RmePUER8oxvVOnTrJo0SK9+KKioqRNmzby8ccfW8yx0RAajUa0Wq3Mnz9fSpYsKQMGDNCbvO3OnTsSFBQkRYoU0XtMdpDyXu3evVs8PDxkxowZevMXpDh9+rR06tRJN6zL0rRv315vFv2oqChZtmyZ1K1bV/z9/fVOQFrK75SUWejr1asnGzdulLi4OPH395fg4GC97eLj4+Xhw4dWMxN4itf/hv7991/54IMPJFeuXHpjyC392PNqntu3b5eOHTuKp6en1K9fX683SXY7cTlixAgJDAyUkiVLypQpU3TL1Wq13L59WwYOHCg2NjbvTU+z9GJh/Z7TaDQyadIkmT17thw9elQKFSokJUqUkO3bt0tcXJxuu8GDB+vNxmyJUg5uX331lXzxxRciInLw4EHJlSuX3kywluCTTz4Rf39/KV++vPj4+MiQIUMkISFBd2DetWuXBAYGire3t3h7e8vMmTPNHHHGpefL9JtvvhE7OzuJjIzMgoiMk/LerFu3TgoUKKDX9e913333nRQuXNhifiC+7qOPPpLmzZu/dRutViuxsbFSsmRJvTGE1uhNEyHWq1dPAgMD9ZaljLHOTMHBwTJo0CC9S9n069dP+vfvLyL6hcmDBw/ExcVFxo4dm+lxZQfTp0+XwoULS5UqVeSTTz6RIUOGSIUKFaRatWry119/iUj2m0TpxYsXkj9/fpk/f75u2bVr12TJkiVy9OhR0Wg08vz5c4sYKpOWzZs3i62trdy6dUtvuVarlYMHD0q/fv2kbNmyEhwcbHHzNERGRkrbtm2lePHiUqVKFfnggw9046u1Wm22+6wZ6+eff5aGDRvqfWe/+l3/888/y7fffpvmOkul1Wr1jqm3b9+W8ePHS+3ataV169Z6PUiyS76jRo2ScuXKybRp02Ty5MlSvHhxuXPnjl58ycnJsmXLFrGzs5NPP/3UjNFmLyys32MpfyB//fWX5M2bVzcjZceOHUWlUsmYMWPk33//FRFJNRNgdrdnzx69SwCkFDUnT56UnDlz6nUrmjt3rtSuXTvbtEC8S0hIiJQqVUoiIiIkLCxMunbtKoUKFZKwsDC97a5duybHjx+Xs2fPmidQA+3bty9dPya0Wq1Mnz7d4sZ/ajQaCQgI0HXZTOssdXx8fKa2WGamefPmiaenp96wknHjxuldWirFgQMHxN/fPwujy3qDBg0SX19f3f2U4+6yZcvEy8sry8frPn36VMaNGyfVqlWThg0b6k6Yfvvtt1K7du1U2z969Ejmz59vcd8BGfXq3+Hp06dl7Nix0qxZM6lXr57MmzdPNy4yO35PHDx4UKpUqSKJiYmSkJAgCxYskFKlSknevHnF3d3dorsPP3v2THLmzCnLly/XLbt9+7auq7SISFhYmMyZM0cCAgLE398/W8/aLvJy6MePP/6o11q5ePFiKViwoAQEBMiuXbv0JlDNLsWWseLi4qRw4cJia2srbm5u8t133+nWWepJ5Le5e/eubNmyRWrVqiWNGzeWDh066F1NYf369dKiRQupW7eufPHFF3oT6JrTkSNHxNbWVv78808ReXmyt0aNGvLZZ59J7dq1pVu3brrvDbVaLdeuXcs2sWcHLKzfQ8+ePUvVKnL48GGpW7eu/P333yIisnr1anFxcZFSpUrJmTNnzBGmwZ49eyY5cuRIc2yqj4+P3thjkZcHv9fPhGdXf/zxhyiKotete/bs2aIoikyYMEEWLVokEyZMkJMnT8qBAwfMGKlhFi1aJGXKlJEZM2bInTt3dMtf/2GRmJiYapbi7GzXrl1y5swZ2b17t1y7dk38/PykadOmcuvWLbl06ZI8fPhQrl69Kmq1Wi5cuCAilvljKiIiQhRFkRkzZuiW/f7776JSqeTQoUNpPubVVlNrc+zYMbG3t9f9QBH5v8KsX79+urHLWe358+eyZcsW3VjGuXPnyrlz56Rdu3ayYsUKmTFjhnTr1k0CAgKkcOHCFjsmN71SiuqffvpJr2ATsYy/w/Pnz4uNjY2EhoZK586dpWHDhjJ37lwREalbt26q7zxLUq9ePd01nVP4+vqm6uXy4sUL2bJlS7aaTflNRowYIW5ubhIaGqpXaF25ckU++ugjKVWqlISGhsqNGzfMGKXpLVmyROrWrSuHDx+Wzz77TGxtbaVTp066SVZThmRYwt/cu8TGxkrTpk2lWrVq0rlzZ+nevbtUq1ZNbG1t9eYEOH/+vAwePFj8/Pzk6tWrZoz4/xQqVEhCQkJ0958+fSoODg7SokULmTBhgvj6+krBggWtZnihqbGwfs+EhYVJrVq1pGPHjjJ58mS5ePGi3gyFjRs31k2aEBUVJTVr1sw2f+zpFRgYKC1atNBbljKp14oVK/QmhbC0A3jLli3F29tbfvvtNxF5+WMiT548UqtWLZk6daq0bNlS6tevL15eXpIrVy7ZvXu3mSPOmAcPHsjgwYOlSpUq8umnn8r+/ft16159r8aOHSt169a1iPdvx44d4u7uLnnz5hVPT08pWbKklChRQhRFEScnJyldurQ4OzuLj4+PuLm5pfoRaUkePXokjRs3FmdnZ5kzZ44kJCRI0aJF9cZnpXh1PLm18vLy0ptU7/nz5zJnzhzRaDRmO8OfciIjLi5OTp48KWPHjpVKlSqJr6+vKIoidevWlcDAQOnfv78sW7bMqi7tk5aUovrBgwdiY2Ojd0LWkj6bCxYskKJFi0r16tXlzJkzuqFcLVu2tNhx1bdu3ZKyZctK8eLFZd++fSLy8thfvnx5i2/RnTp1qhQsWFA6dOgge/bs0Rs/PX78ePHx8ZFPPvlE74oKlkytVsuWLVvkq6++koSEBNFqtfLLL79IqVKlpECBAnrf9cuWLdOdYLZUn3zyibRp00bXWCXy8hKL06dPF0dHR+nRo4eulT4uLk7v8nHm9NNPP4mdnZ0EBQXJ77//LiIijRo1ktatW+t+O2u1WilQoIBFDjHMCiys3zNdunQRRVGkXr16UrRoUWncuLH4+/tLly5dZN68eaIoioSGhmaLGQkN8fXXX4uHh4fel9TYsWMlNDTUjFEZL6WV67vvvpP27dtL7dq1ZcaMGfLhhx9K9+7ddT+WU34k3r59Wy5evGi2eA3xahfL9evXS61ataRBgwayaNEivevGHjhwQBRFMVtrX0Y9efJEoqKi5O7du/L06VP5559/JCIiQmrWrCmfffaZXLt2TU6cOCGXLl2SXbt26V1H15K8+uN20aJF4ujoKE5OTnrXVn+fDBo0SAoWLKj3uqT8vWaHQqBixYpy7NgxefDggaxatUpatGghpUuXtuhrpqdXWq9/SstSdvdq7BqNRpKTk3Xf1xqNRtdlPyYmRtasWSPOzs4WMQdFWl68eCHHjh2TTz/9VNzc3KR169bi4uIily9fFhH974zs8DeVHq/+tjp27Jj4+/tLhQoVZNGiRXrDf/bt2ye1a9fO9t3aM+rV7u8iLxt7+vTpI4qiyKhRo2Tr1q2iKIruPbZEc+bMkXz58qX5XR4fHy9Lly6V/Pnzy/Hjx80Q3ZulfNY2bNgg1atXlxYtWki7du3E29tbdyI4MTFRkpKSpGnTpjJp0iQzRpt9sbB+z4SHh0unTp2kbNmyMnPmTNm4caOcO3dOgoODpU+fPlKgQAHduJfsNkPhu0RGRoqiKDJixAjdGN1jx46JnZ2dxV+q4dXLv1y5ckVCQkKkUqVK4uTkpHdJo+Tk5Gw5BjC9Xo396tWr0r17d/H395ehQ4fKH3/8IU+fPpVSpUrJgAEDzBilafTq1Uvq1KljdZPTpLh8+bI0a9ZMcubMKevWrbPoz2VGPXnyRAICAqRatWoye/ZsSUpKkqVLl0qRIkV081ZklZSCIyEhQdd6sm3bNilXrpzeBJWHDx+WIUOGiK+vr/Tq1ctii7E30Wq1uu+0hIQEiYmJ0c1L8fz5c/niiy9S/ejPjlJy2LZtm3Tt2lXq1KkjQ4cO1Rv6Ex0dLdOmTZOiRYvqjWO1VPfv35fFixdLhQoVxN3dXa/7tKX9Tnl9LHFSUpKMGjVKvLy8ZODAgXLo0CG9lkFr8bZc4uLi5LvvvhMPDw9RFEW+/PLLLIzMtMLDw0VRFF0LfFrf7xqNRkqUKJGtJs19/vy51KxZU0JDQyU2NlZu3bolXbp0ETc3N2nVqpVey/vff/8tefLksfgJjTMLC+v3xNWrV/XOAM6YMUMKFy4sbdq00V3mRqPRSHx8vLlCNInu3buLg4ODDBs2TG7evCk+Pj4WfZAWeTlWx8fHRxYuXKj7ckpOTpb169dLo0aNpF69ejJ37lzdOCVL9/oPj3nz5knVqlWldevWUrVqVSlWrJiZIsuYhw8fyu3bt/W+kF51/fp1KVq0qO5HoiX/iLp48aLs3bs31Rn4pKQk+fzzz0WlUknXrl3TvD6wtYqIiJCgoCCpUqWKtG/fXhwdHeWnn34SETHLOML69evL+vXr5eLFi7JixQoZOXKkbkxjirt378rXX38tpUuXlqVLl2ZpfFmpc+fOUqZMGalevboMHjxYr1t+dj4BlFJEnjlzRjdT+1dffSUVKlSQMmXKyKRJk3TfAwcOHJAtW7aYM1yDnT59WmbOnClr1qzRLYuNjZX9+/dLq1atJE+ePHrzOGTn9yzFgAEDpE6dOtK9e3cJCgqSJUuWyHfffSc3btyQp0+fyvfffy/FihWTli1bypIlS6yupTotrx57EhISpGbNmhZx6cy32bNnjzg6OkqdOnX05u55/Xhfv359+eqrr9JcZw4zZswQRVF0w4BS5lZasmSJVK5cWVq1aiWbNm2ShIQEqVSpEmcBfwsW1u+JAgUK6M2qKfLyy6tWrVpSqlQpmT179hsvCWNptm/fLrlz5xZFUaRChQp6s9lmhwNYRjVo0EB3wHv9xMepU6ekf//+UrNmTenXr5+cPn3aTFGaRsoPx5iYGBk7dqzuR+Iff/whTZo0ERcXlzcWqtnJX3/9JR9//LHky5dPAgMDdX97KZ+/Fy9eiFqtlipVqkj//v0t8nOZYsyYMVK5cmVxc3OTqlWryqRJk+TFixd6OR05ckRKly4tDg4Ocv78eTNGm/leb0FbuXKlBAQESNGiRWXp0qV6raKZXRCk7H/WrFni7OwsT548kZ49e4qiKFKqVCndkJnXr2ud3booGuPvv//Wu/7xyJEjpUyZMrJ06VKZPHmy1KhRQ3x9ffXGkmf3XiTVq1fXjZv+559/xMHBQTp16iRFixaVLl266C4LZon++usvqVWrlgQFBelO+qfMkSIicuPGDfnyyy+lcOHCUqtWLbl//765Qk23u3fviqIooiiKdOrUSerWrSt16tSRPHnySMmSJcXBwUF3wkBRFKlcubJFfye8Scrf1bNnz1KdQN+yZYuoVCqLP/makJAgf/31l9StW1ccHR31fnenHI+fPn0qLVq00Ls8nrmdOnVKvLy8pGzZsvLRRx9JvXr15JtvvhGNRiN//fWXNGnSRAIDA6VixYpStGhRc4ebrbGwfg907NhRAgIC9Ja9eoZ+zJgx4u3tLb1795bffvvN4rpWJSYmyoMHDyQ8PFx34IqPj5dOnTqJjY2NTJkyxSK+fNMya9Ys8fb2lr///lsKFy4snTp10uu+KfLyID1//nypXLmyDB482EyRGu7VVvgUDRo0kIYNG+oVHvHx8RYzQ33BggVl5MiRsm3bNunevbt89NFHIvKyFftVy5cvl5IlS1rspSo2b94srq6u8vvvv8uff/4pLVu2FB8fn1SXfhN52dUsJCQk2xctxnr69KlERUXJlStXdMsuX74sXbp0kSpVqsiwYcPk1KlTmR5Hyt/O7du3xcbGRk6cOCEiL7sqfv311+Ls7Cwff/yxPH78WESs85q5IiJr164VZ2dn+eijj+TKlSsyb9483eSParVajh49Kn369BFvb28ZMWJEti1oUgqRM2fOSK1atXQnwn19fWXixIkiItK2bVtxdHSU8uXLy71798wVqlF8fHxkypQpus/l48ePxcfHR8aMGaP7bfL06VPZvn27+Pn5yc6dO80Z7jslJibKjRs35I8//pAaNWpI4cKF5dixY/L8+XNJSkqSixcvyqlTp2TZsmWyevVq+fTTTy3+BHlaXv27KlWqlN7lUEVeXjnDEq9k8iaPHj2SyZMni729vTRr1kyvgefbb7+V/PnzZ7uhJzt37pRPP/1Ufv75Z/n000+lfPnyMnToULl9+7YkJCTI559/Lt7e3npDMSg1FtZWbtOmTeLo6KjXJeWbb76RyZMn63Ud3rt3rxQuXFiaNWuWbX9YvMmYMWOkfv36utlcX50cZNGiRWJnZycff/yxnDx50qImZbt+/brY2trqJulatmyZlChRQnfpG7VarVd47t271+LP9oq8bOFzdXWVu3fv6pZZ0smeTp06Sa1atXT37927JxUqVJAOHTpIxYoVpU6dOrrcLl++LOPGjTNXqEaJiYkRJycnvVmUv//+e1EURZYtWyYHDx6UXbt2SWRkZJaPKzaHJ0+eyPz586VUqVLi7OwsZcuWlebNm+v1BJo5c6ZUr15dGjduLOvXr8+SY23NmjXFxsZG78d6XFycHD58WNfT4Mcff9Sts7Tj/7vExMTIb7/9Jo0aNRIPDw8pU6aMrFq1Sm+bO3fuyKJFi6RQoULSqVMnM0X6ZqtWrZIePXrI9OnTRUTk119/ladPn8qGDRukRo0auuP+smXLpEOHDhZboAwdOlSqV6+ud7yvU6eO+Pr6ioeHh/j7++tmi9ZoNBZx8qBhw4a62ZOfPXsmn376qdjY2MiQIUNSnSS3Ju3atZNvvvlGdz/luDJmzBgpU6aMXi8Ea7Bp0yZp27at3lV0NBqNHDhwQMqXLy958+aVX3/9VdRqtbi6usrKlSvNGK2+lL+3e/fuScOGDaVPnz4i8rIbuL+/vzRt2lR+/vlnERGr+I2Z2VhYW7GYmBhxcHDQm9zq6tWrYmdnp+v29uoX2LNnzyzu0loDBw6UJk2ayK5du3TLVq1aJXv27NHdDwsLk6pVq+pNKGEJKlWqJP369dPdT0pKkmbNmknBggX1WgQtYXzZ6x49eiR79uyRRo0aSatWraRLly66s6Dff/+97tIqliZlRtNXu6tPnz5dnJ2dZfLkybJmzRqpWrWqFC9eXO863Zaod+/ekjdvXr1eBH5+fuLq6ipDhgwRHx8fqVGjhuTIkUM8PT2z1Q+JzNCiRQtp3ry5TJgwQfbv3y9TpkyRatWqiZOTk14hd/z4caldu3amXm835ZgwYsQIyZcvn3Tt2lUKFiwon3/+uW4btVot4eHhMnz4cHFwcJDWrVtbXVH9qitXrsjEiRPF29tbAgICUo1hjYuLk927d+uOrdnltVi6dKlUrlxZ5s+fn+qYsXz5cvnggw90RcqIESNk2LBhZojSeI8ePZKPP/5Yb1z1gQMHpEKFChIVFSU3b96Uli1biqIoqa41nl2lDMF4/bO2bds28fDwkPLly+t6kohkn8+csbZs2SKKoujNci7ysrdMpUqVdF38U1h63qNGjZIWLVroDTm5efOm7jh87949GTx4sNjZ2YmiKNK4cWNzharn/Pnzuka3lFogKipKatWqJYsWLRKRl8O4WrVqJT4+PrJ+/XqzxWpJWFhbsS+//FIURZF169bplvn5+aXZXThlTJ0lHeB+/PFHcXZ2litXrujinj9/viiKIg0aNJAVK1bonV2bPXu2xXR1vH//vkycOFF3YH71jGLlypVl2LBhugmQLOk9S9G+fXupVq2aNG/eXDdUQaVS6SbzELHMEwZffPGFKIoio0ePlv/++08uX74szs7O8sMPP+i22bNnjxQoUMBir0+a8nmbO3euBAQESPPmzeXnn3+WIUOGSKVKlSQ8PFxEXnbdj42NlWPHjum1aluj0aNHS5kyZeTWrVt6f7OXLl2SAQMGSJEiRfQK6ZTL42WGlPfn4MGD4ujoKOfOnZP79+/LtGnTpFSpUvLRRx/pnfh5/vy5bN68WcqWLWt1rUgi+seRqKgo2bp1q/j5+UnBggVl27ZtZozs3W7duqU36Z2Ifj6nT5+WihUrSpMmTaRXr17i4OBgsdf/jY6OlsKFC+u1ct69e1fvJPKDBw+katWq8u2335ohwoxJGYJx8uRJEUk9KWdERIS0bNlSnJycZMqUKVYz+eizZ8/EyclJVqxYoVsWGRkp58+fl4SEBKubY2Pr1q2SN29eOXv2rK5H5Pz588Xd3V0WLlyom8ciKSlJvv/+e2nZsmWqz4I5/PXXX+Lk5CTOzs7Sr18/mTJlimzatEmSk5Nl+vTp0qJFC13PutjYWJk8efJ7MaGeKbCwtmKHDx+W4OBgKV++vAQFBUm/fv3E399fnj17pleQDRs2TIoXL27maDPmxYsXUrt2bV3XOJGXLRKKosiiRYukS5cuUrlyZRk6dKicPXvWjJEa7k0F85w5c8TBwUGv+6Yl6dGjh9StW1dvgp179+7J7NmzxdHRUTp16mRRXfZft3XrVnF2dpYqVapI8eLFZdCgQXrr7969K+XKldON87Q0r56c+uOPP6RVq1ZSvnx5cXBwkLVr1+pta4knfTLq2LFjYm9vr9fV+tWeQNevX5fq1atLmzZtRCTrJsYqW7asboIrkZc/eH/++Wdp2rSpFC5cWL7++mvduqSkJN0PQGvx+om5lM9iUlKSnD17VgYNGiR58uSRgQMHZtvPaZ8+faRbt25prkuJed68eTJo0CBp1aqVRZ/ASkxMlICAAJk9e7aIpH3siIiIkBo1aljEbOcpQzBe/Z5L629/yZIloiiKxX6fv+7jjz+WZs2a6S0LCAiQOXPmmCmizBMfHy8lSpTQm4Ts8uXL4uTkJG3bthU7Oztp06aNrjdeUlJStun+HxoaKu7u7hIQECD16tXT9eZp0KCBtGnTRhRFkY4dO1r0bzFzYWFt5e7duycLFy6UOnXqiI2NjUydOlVv/cGDB8XW1taiik+tViuPHz+WqlWr6loCtVqtnDlzRjeJi8jLAtTZ2VnvbL8le/WH4sCBA6VChQpy6dIlM0aUcd9//704OTmlOeQgMTFR1qxZI15eXhZZdMbHx+taIp89eybNmzcXRVHkf//7n0REROh+KI4cOVLKly9vzlCNMmXKFNm6davuCzcxMVGmTZsm5cqVk06dOsnWrVv1zshn16LFVHx9faVGjRq6+68W1Sm5//DDD+Lu7q43gU1me/V48ep7cPHiRfnss8/Ex8dH2rdvb7ETO77Nq/muXLlSgoODpVmzZnpdiB88eCCrV68WHx8f8fPzyxatSClS4m/fvr2MGTNGb9nrBgwYYNHfcd99952u+/fYsWPFzs5Ob2jXq8XoiBEjLOLY+foQjPHjx+vWvX6JOxHRm0/Ekh07dkycnZ2ld+/eumJyzJgxUrp0aXn27JmZozO9Q4cOSY0aNeSff/7Rvafjx4+XgQMHisjLY+0HH3wgBQoU0PXkyi40Go1s27ZN2rRpI61atZLVq1dLcnKy7NmzR9avXy+ffPKJ7N27V7ctpR8L6/eAWq2WvXv3Sq9evaRs2bIyYsQIXQHg7e2tV4xaioiICHFyctJNqPDqF1XKQeD58+fStGlT+f77780Soym8/gWcktvp06fFzs7Ooq41+/z5c1EURdeN700td5UqVZJevXplZWhGefDggYwaNUoaNmworVq10hvfv3TpUrG1tZWPP/5YLl26JPv27RNFUSy2G/jNmzflgw8+kDp16si8efP0JubatWuXNGjQQGrXri2hoaFy48YNM0aaNSIjI2X06NFSsGBBadasmd6s768W2CtXrpTAwEBdbyFzePV5Hz16JBs3bpSKFStKYGCgWeLJTCmv/Zw5c6RYsWLSpUsXGTZsmCiKIr1799a9TwkJCXLw4EH5/fffRSR7nQTSaDRStWrVtx4L//vvP+ndu7fFtnZeu3ZNb+6T//77T9q1aycffPCB3nwA4eHhMnfuXMmVK1e270r8tiEYr86mbEkTcqbX06dPJTQ0VBo0aCDNmzeXzz77TFxcXHTvWXb6+zKF/fv3S65cufSGHEZGRupdbvLYsWMSEBAgly9fNleYbxUWFia9evWSatWqydixY1OdaLW29ywrsLC2MkeOHJFp06ZJUFCQHD9+XK97340bNyQ0NFSqVasmTZo0kVq1aknlypXNGK1hUorL5s2bS5s2bd54neqdO3dK4cKFLfb63CmF5+XLl/UmoEuxf/9+ixkzLvJyaELOnDklICBArl27plv++tnQtm3bSkhIiIhYxkG9atWq0qZNG+nfv780bNhQSpQoodf97+bNm1KxYkVxc3MTRVFkypQpZozWeI8ePZJ+/fpJ+fLlZeDAgXLo0CHduqioKBk+fLiUKlVKBg4cmK1aATPLo0eP5Mcff5RatWpJwYIF9cZSp+Q/ceJEadWqVbY6869Wq+XYsWNWdwIk5Zhx69YtcXV11V2OadasWeLp6Sk+Pj5SpEgRXWtMdjZz5kwpXrx4qsvbvJpjuXLl9P4GLUmZMmV0rXspVq9eLf3795ciRYqIq6urfPLJJ5I3b14JDAy0iAkQ3zUEY+HChbp1lvT9nRG7du2Szp07S/78+aV69eoSGRmpW5edjoHG+vvvv6VgwYJy5MgREUn798rmzZulSpUqeq9BdpOUlCRLly6V2rVrS/PmzfXmhKGMY2FtRU6cOCGFCxeWpk2bSrFixcTNzS1VF7G4uDjZunWrNGnSRDw8PCQiIsI8wRro1Za+b775RhRFkZCQEHn69KneQe3WrVtSsGDBVF3fLcWrXz7FihWTBQsW6O5b6oRliYmJcurUKencubPY2dnp5ZRy9j4+Pl66dOkikydPNleYGTJ8+HDx9fXVncDatm2bKIqim7jl1cmgQkNDpX79+maJ01RebWVZuHCh2NvbS/369WXFihV6x5IVK1ZY7I/99IqOjtb9MNZoNHL+/HkJCgqSPHnySO/evXVd5S9duiTOzs7ZaqZ7Szx+ZNTcuXN1l425dOmSuLq6yq+//ipXr17VneQaO3asmaN8u3/++Ue8vLykZs2a8vfff+u9b48fP5Z69epJu3btzBih4YYPHy6lS5fWm8ivW7duEhoaKk+ePJG9e/fK9OnTZdiwYbJgwQKLuWRfeoZgdOjQwaqGYDx79kyioqL0Wm7v3r0rkyZNkg8//FBatWqld71xazn+xMfHS/Xq1eWDDz7QNeC8mltUVJQUKVJEQkNDzRVihly8eFHatGkjgYGBMmLEiGwzHtzSKCIiIKvg5eWFoUOHYtSoUbC3t0f58uUhIjh37hzs7Oz0tr18+TK0Wi3KlStnpmgzrn///ti7dy9u374NGxsbAMDKlSsxcuRIlCxZEoMHD0b+/Plx6tQpHDlyBI6Ojvj111/NHLVx2rdvj6ioKOzbtw8ODg7mDscgUVFRWLZsGc6cOQM3Nzc0a9YM0dHRGDlyJGrXro0NGzYgT548AIDffvsN3bt3x7Fjx/DBBx+YOfK3O3PmDKpWrYqjR4+iVq1aAICNGzeiW7duaN68OZKTk/H8+XN4e3vDy8sLbdu2Re3ataEoipkjN5y8PBkLGxsbNGvWDElJSXBzc8O1a9fQsGFDtG/fHlWrVjV3mJluwYIFOHHiBNzd3bF48WLd8qioKOzZswezZ8+GWq3GihUrMG7cOJQqVQqrV682Y8Tvn+PHjyM8PBydO3dGp06d4OzsjJUrVyI+Ph59+/ZFqVKl8PHHH6N27drmDvWtrl69ii5duuD27dsYPHgwihYtiidPnuDw4cO4f/8+zp49m+r7PbtL69j5/fffY8CAAThx4oRF/S55FxHRHfMfP36Mffv2YcaMGXB1dcXhw4fNG5wJnD9/HlOnTsXRo0fx4YcfYsCAAWjYsKFu/caNG7F161Y8ffoUtWvXxsiRI+Hq6mq+gI304MED3LhxAzY2Nvjwww9x9epVdOvWDeHh4fjyyy/Rt29fJCcn48iRI1i4cCGePn2Ko0ePmjvsdIuPj8fUqVPx8OFDfPPNN+YOxzKZs6on0+nYsaPUrl1bRP7vjJm/v7/kypVLFi1aJC1btpTZs2fLokWL5LfffpOYmBhzhpthR44cEQcHB72Zd1MuT3Hq1Clp1qyZ5MmTR9zd3aVkyZIyffr0LJ0oyFhpzWAbExMjtWvXttjxuCmqV68uDRs2lIYNG0rTpk3F19dXtm7dKocPHxY/Pz9xc3PTjZUvXLiwxbRWh4aGSqFChWTIkCFy/fp1UavVkidPHhkwYID8+eef8t1338n3338v7dq1k8DAQNm8ebO5QzbIsWPHdNdaTWmxnjVrlhQqVEji4+NF5OWl7CpVqiT169eX7du3my3WrLB8+XLx9/eX77//XjdWd/f/a+/O42rO9z+Av85plYm4KFsiMtbEQ/aRXd0QNxHC3EuyjLIv95GsjZixjMRouFyMa7mMGQ0uhcnWpUTXRRGyRbK3SOe8f3/4nXMLsxjL1/f0ev75Pd+Hxyt1vt/v+/N5fz+fH380ztbk5+fLkSNHJCAgQDQajVStWlXJuCWa4T7n6+tb7LrSqVMn+fHHH5WK9dpu374ts2bNkqpVq4qTk5NUrlxZZs+eLefOnVM62u9S9NqZlpYmhYWFUqFCBVm5cqWI/O86k5mZKRMmTJDc3FyTmeU0tVcwHB0dZdSoUbJq1Spp3bq1/PGPfxQRKbZYWXJysowdO1YaNGggCQkJSkV9Y4mJidK8eXOxt7c37kd969YtSUlJkaFDh0qpUqWkUqVK4uTkJI6OjtKvXz+5e/eu0rF/F8O9nV4fC2sTcP36deOX/Pbt2yLyvA2uXLlyMn78eFm7dq0MHz5cevbsKVWrVpVGjRqp7j2XSpUqFXswunv3rnTo0EGuX79uPJaamipZWVmq2mvv8ePHxd6z+rWHB7U9XISEhEiDBg3k3r17IvK81ahx48bGLaiuX78uISEhYmlpKdbW1tKsWTMl474Ww6qanTp1Ei8vL6ldu/bPtmWqaZDnRf7+/qLRaCQiIkJEnn/PXrXa/rFjx6Rdu3aq2mHgdV2+fFlsbGxkx44dxmvoTz/9JBqNRipVqlRsEan09HRZsmSJXLp0Sam4JUbR+1lubq5cv37deF0tLCyUgQMHSsWKFSUyMlL69u0rTk5OSkV9I48ePZLs7Gzj9VStfunaWXTV7I4dO0rPnj2VjPpWqe3+/Wv69esnbdq0MX7/UlJSpG3bthIYGCjdunWTvn37Gge38vLy5ODBg0rGfWPVqlWTKVOmyMGDByUhIUGcnZ2lY8eOIvJ88Ov06dMSEREh33zzjSQkJMiTJ08UTkxKYGGtcvn5+ZKamiqHDx+WevXqSc2aNWX58uVSvnz5l1YKNXzJDcW3Wvj5+UmnTp1ERIrdcA37wv7cfqVqEBgYKP7+/sVWjDT8PEXfZ33y5InqRhBPnjwpGo1GDh8+LCL/W6hl9uzZ0q5dO2PHQX5+vmzdulU6d+6sur9NEZGrV6/KkCFDpGrVqjJs2DC5cuWK8TNT2QNy0aJFYmVlJV5eXlKvXj0ZO3as8bOiD8JqG7B7Xf7+/tKvX79ix+zt7WXSpEkyfvx4MTc3l2HDhhm/qyVh8bYPSVhYmDRt2lQaNWokH3/8sXFfZ51OJ4MHDxZ7e3vx8fExdgGZ6uJRalH02jl8+PBi184vvvhCypYty+/QB2rr1q2i1WqLTW7MmTNHbGxsJDg4WMLCwqRBgwbi4eGhurV8XqV///7SoUOHYsdWrVoldevW/aAXJqP3j4W1ynXt2lUWLFggIs9Hs4cPHy4ajUacnZ2NhfSLD71qKjzT0tJEo9HIwIEDjccWLFggjo6OxsU/DD/P6dOnjcWaGuj1epk/f754eHhI9+7djQ+BIsULlKdPn0pQUJBERkYqEfN3M7T7jRkzplgLv4uLS7F9PUWeDyKo7fWEop49eyYrV66U9u3bS48ePVS9r6xBTk6OpKenGxdmS05Olvbt24tGo3nlNm+mXlTn5uaKj4+PLF++3HgsISFBpkyZYhxA2bNnj2g0Gpk7d65SMUscw/V/y5YtYm1tLUuXLpXo6GgZN26cmJubi7+/v/Hc7Oxs433R1P9e1aLotdPb21t2794tFy9eFEtLy2L7WdOH5bPPPhONRmNc5fzChQtia2srW7ZsMZ4THR0tVapUUe3OLAaJiYnF7nuGa86OHTukQoUKxi5JNT1b07vDwlrFFi5cKLa2ti+1PsfExIi9vb00btzY+G6kGj169EhGjhwpmzZtEmdnZ2ncuLF89913Ur58eWPhYriQpaSkqGp/4AsXLkhUVJTo9Xo5fvy4+Pn5ScuWLWXSpEly7dq1YucuXbpUNBqN6kZFi7b7Gd69nTZtmjRq1Mg4AGJqD7emsqpmRkaG9OjRQ+rWrSt2dnbG98Pz8vJk+vTpYmZmJv7+/iYxE/Fb5eXlSZ06dYxFs2G2s+hg3uPHj2XAgAHFttShd8dw/SgoKJDQ0FD58ssvi322d+9ecXJyktDQUM5Of+CKXjstLCxk2LBhSkeiX1G0k+njjz82djIZvpdpaWnSuHFjY9eaWmVkZMjo0aPF0tJSPv30U+NxJycnmTdvnoiY5r7k9PuwsFap9PR00Wq1cuzYMRF5ueXw1q1b0qtXL7GxsZHZs2eraibXIDY2ViwsLCQ6OlrOnDkjnp6eotFoxM3NzXiO4QLu5uZm3FpFDcLDw8XFxUVGjhwply9flocPH8qsWbOkVatW4uPjYxypv3DhgtjY2Mjq1asVTvz7Xb16VYYOHSpubm6i0Wjk22+/NX5mijejnJwcmTp1qqr+Hl/k6uoqAwYMkPXr10twcLDUr1+/2DXkyJEjUrduXalVq5Zx4TlTV1hYKP7+/tK+ffuXjhtcvnxZatWqJbt3737P6Uq2iIgIcXNzk7CwMOMxw6BrSEiItGzZ0iSvNaYmJydHpk2bJj4+PkpHoZ/xOp1MEyZMkCZNmigR863Lz8+Xf/7zn1KjRg2pW7eudO3aVbp06SIFBQUmN0FAb4aFtUq1bt1atFqtnDx50njsVSPyUVFRotFoXnrfWg0ePHggAwcOFHd3d3n06JHodDqJiooSW1tb8fDwML7bM2HCBKlRo4ayYV+TYTa3Q4cO0qlTJ9m2bZuIiOzevVu8vb2lTZs2MnPmTHFzcxNvb2+F0765goICWbVqlbRo0UJ8fHxMolX616jtnXiD4ODgYvvLXrhwQVxdXeWzzz6TmjVryrBhw+TEiRPy4MED6dWrl3h5eSmc+P05ceKElC9fXnx9fV/aVzcrK8vkFlv6EN26dUvi4+NF5HnxfPPmTfH19ZXq1auLs7OznD59utj5e/bskTp16qi+HbUkUeNEQEnwWzqZ+vfvL48fP5b4+HjRarWq6SL8rS5cuCABAQGi1Wpl+PDhxuMcuCMDFtYqNG7cOKlYsaIMHDhQqlWrVux91aILCRm82FqsJrdv3xZnZ2fx8fExFtfHjh2T1q1bi52dnUycOFEsLCxUuxKxYTbX3d1dJk+eLNnZ2XLjxg2ZOHGiVK9eXRwcHExq8RZTaZU2VS8uOCci8u2334qZmZlMmTJFIiIipFq1atK2bVvj785UFmj7NXq9XgoKCmTJkiXi6uoqrq6u8vXXX0taWpqsWLFCBgwYIHXr1i0x/x9KCQkJkWnTphU7lpWVJUuXLpVmzZpJhw4dZNWqVSLy/CHY29tbunbtqkRUIpPyWzuZnJycxNraWmbOnKlg2reraOFcWFgo0dHRYmdnJy1btpSLFy8qmIw+NCysVSYuLk6sra3l1KlTcuPGDQkPD5e6deuKh4eHnD171niemkfPDAMDhp9h8+bN4uLiYmw51el0cuvWLZk+fbpoNBqZPXu2YlnfhoKCAlmxYoW0bdtWvL295cCBAyIisnHjRklOTlY23DtgCq3SpupVe3NXrFixWIvf6dOnxdraWuLi4hRMqpzCwkL5xz/+If369ZNSpUpJhQoVpEyZMjJ+/HiT/L5+KAztlkUfYidPnlxsUDUmJkb69+8vlSpVkqpVq4qHh4cEBwcbH/7VfF8kUtJv7WR6+PChDBo0SLp06aJw4ndj2bJlcvfuXdHpdJKUlCRdunQRjUYjZ86cUToafSA0IiIg1WjYsCG8vLywYMECAMCjR49w4MABREdHIyUlBZMmTcKYMWMAAIWFhTA3N1cy7lszcOBA7Nu3D3FxcWjYsCEAIDc3F+fPn0fTpk0VTvd2pKSkICwsDHfu3EH79u0xa9Ysk/n9vUpeXh5KlSqldAwqQq/X47vvvkNUVBSsrKyQmpqKJk2aYOvWrdDpdNDpdMjOzoanpyfmzJmDHj16KB35nRIRaDQa6HQ6mJmZQa/XQ6vVAgDu378PvV6PtLQ0VK5cGTVq1FA4renT6XTYv38/unXrhtTUVPj5+cHMzAyBgYEYMWIEAODKlSv4+9//jm3btqFGjRoYPHgw+vbtC+B/v08i+u0SExPRvHlzxMfHo02bNgCATZs2ISAgABMnTkT58uWxbNkyODk5Ye/evbCxscGzZ89gYWGhcPK3w3D9X7ZsGZYsWYLjx4+jYsWKAICsrCzExsaif//+CqekD4aydT29rqKLJBRt+T5z5oxMmzZNnJycxM/Pz7gVlZqcP39eZs6cKZcuXXppBezc3Fzx8PCQoUOHGrdLMUWG2dyhQ4cqHYVKsF/aX3bRokXi5ORk0qssv9g186rP6P1bu3ataDQaGTVqlIg8X3V49OjRUq9ePRk6dGix+96GDRukT58+0q5dO5k1a5bcu3dPqdhEqlaSOplSU1Pl+PHjLx2/dOmSlClTRrZu3apAKlITzlirnBQZgb979y727duHiIgI2NnZ4eDBg8qGe03jx4/H5s2bcefOHbi7u6NcuXIYNGgQHBwc0L59e2zduhWBgYFYs2YN+vTpo3Tcd4qzuaS0wsJCrF69Gps2bYKtrS1Gjx6NOnXqoH79+tixYwe8vLyUjvhO5OXlQURgY2MDT09PdOjQAZMnT1Y6FgG4desW9uzZgy+++AJmZmZYt24d3NzcsGrVKqxduxYigkmTJhnvD2fPnsXq1asRExODOXPmwM/PT+GfgEh9SlInk6OjI+bNm4eAgIBix5ctW4bU1FQsW7ZMoWSkFiysTYxOp8Px48dhb2+P2rVrKx3ntej1euTm5uLEiROIjY3F+fPnERcXB3t7e+Tn52PYsGGIiorCkydPcPjwYTRq1EjpyEQmLyUlBTNnzkR2djaOHj2KIUOGIDo6WulY70zHjh3RunVrfPTRR5g/fz4uXbqEP/zhD0rHov+Xn5+PEydOIDIyEnv37sXUqVMxdepUJCYmYunSpThy5Ai8vb2xePFiaLVa5Ofn48cffzT5wViidy0jIwMzZszA/v374eXlhb/+9a/GV2AWL16Mr776Cmlpaap9ha1///5ITU1FUlKS8VhmZiYcHBwUTEVqw8LahIgJvT9m+Flu3LiB5ORkpKSk4Pvvv0dOTg7u37+Py5cvw8zMTOmYRCVCbm4u5s6di3PnzmHHjh1Kx3mn1q1bh1GjRuHZs2cIDQ1FaGjoz55rStfcD9njx49ha2tb7FhWVhbWrl2LFStWoHr16ti4cSPKlSuHzz//HC4uLhg8eLDx3UgiejtMtZNp27ZtGDRoEK5du4aKFStizZo12LVrF5KTk+Hg4ICwsDB07doVGo2G1336RSys6YNVdKEgAHj69Cnu3r0LS0tL48IRRPT+5Ofnw9raWukY71ybNm1w7tw56HQ6hIWFISAgoNg1Jzs7m7PY75jh4XX16tXYunUrnJycUKtWLVhZWcHd3R2lS5dGhQoVEB8fj40bNyIxMRGLFi1Cv379Xvo3iOjtMqVOpvz8fNSpUweNGzdGTEwMtm/fjmnTpuGTTz5B69atsXPnTsTExGDNmjUvtYgTvYiFNanCi0U2EdHbZpjhTEpKQtOmTTF37lzMmDEDPXv2xJw5c9CwYUPk5eWhXr162LlzJ5o0aaJ0ZJN29+5dNGrUCLdv34adnR06d+6MlJQU6HQ6XLt2DQ0aNMCtW7dQoUIFpKSkAHi+WnvZsmUVTk5k+kylk+nRo0cICQnBhQsX4OTkhH379mHOnDkIDAw0DsxNnjwZ27Ztw4kTJzioSr+IhTUREZVohoL66dOn0Ov1MDMzg6WlJQDg1KlT6Nu3LwoKCjBgwADs27cPDg4OiImJUTh1yXDw4EF89dVXMDc3R+PGjTF16lQ8evQI9+7dQ2JiIrRaLY4fPw4AaNGiBfz8/NgCTvQemUon07p167BkyRLUqFED0dHRqFixorHrZePGjZg/fz7i4uLYMUm/iIU1ERGVWEXbhYOCghAfH4/69eujXbt28PX1RZUqVQAA48aNQ0pKCmrVqoXly5ebzB6tapCdnY05c+bg+PHjcHV1RVBQENzc3H72fLaAE9GveVUnZHp6Os6cOQNvb2+Ym5sbz9m2bRsiIiKwe/duVKhQQaHEpAYsrImIqMQbPXo04uLiEBAQgBMnTuDOnTuoXbs2AgIC0LlzZwDP24xLly5tnM2m90ev12P79u1YsWIFzMzM0K9fP/zlL38BwEKaiF7f559/jk8++QQtWrT4xZXMs7Ky4O7ujhEjRmDq1KnvMSGpEQtrIiIqkQyzEZmZmZg1axYGDRqENm3aAACio6OxZcsWaDQaeHt7Y+jQoShTpozCiSkjIwNhYWG4ePEimjZtirFjx8LZ2VnpWESkIrNnz8bMmTNRrVo1hIWF4U9/+hPs7OxeOi8mJgbh4eEoVaoU9u/f//6DkupwNSgiIiqRtFotdDodZs6ciX//+98oLCw0fjZ8+HCEh4ejevXqWLlyJZYvX65gUjJwdHTEqlWrMGjQIOzfvx8HDx5UOhIRqUhGRga+//57REdHw9fXF8OHD0dwcDDOnz8PvV5vPE+n08HR0RGenp7YvHmzgolJTThjTUREJVZSUhKmTJmCpKQkeHh4YPny5XBwcDB+npOTg8jISPj7+8PR0VHBpPSi1NRUuLi4KB2DiFTkv//9L7755hv4+fmhZcuWOHToEPz9/VG6dGlERESgW7duKF26NK5fv46TJ0/C09MTVlZWSscmlWBhTUREJVp6ejrWrVuHH374Ac7Ozhg2bBi6deumdCz6jfiONRG9juvXr6NatWrFjg0YMACbN29GSEgI/vznPyMgIACtWrVitxK9FhbWRERUYhTdiklEkJOTg48++ggAsHnzZmzcuBEPHz6Et7c3goKCYGtrq2RcIiJ6hwoLC42Ll23evBlBQUHQ6/WwtLTEzZs3uQMEvRYW1kREVCIUndmcMWMGTp06heTkZHTq1AmjR49G8+bNcfr0aaxZswaHDh2Cu7u7cRVqIiIyTUUHXHfu3InevXvj0KFDaNeuncLJSG1YWBMRUYlgWAV81qxZ2LhxI0JCQuDi4oKuXbti8eLFCA4OBvD8veqoqCi0aNECn3zyicKpiYjofbhz5w6aNGmC7t27Y82aNUrHIRViYU1ERCVGRkYGWrVqhfXr16Njx45YsmQJVqxYgYSEBNjZ2SE5ORlNmjRROiYREb1nmZmZiIyMxNy5c5WOQirF7baIiKjEyM/PR82aNdG+fXscPXoUoaGh+Prrr2FnZ4fU1FRMnz6d+5USEZVADg4OmD17ttIxSMVYWBMRkUkzNGaJCGxsbHDlyhXs2rULQUFBGDduHDw8PAAADx48wKVLl2Bvb69gWiIiUopWy9KIfj+2ghMRkclLSkqCVqtFkyZNsGjRIixcuBAWFhZIS0uDlZUVbt68CS8vL7Rt2xaRkZFKxyUiIiKVYWFNREQmKTY2Fnq9Hl26dIFWq8Xf/vY3DBkyBFeuXEFkZCTi4uJgYWGBqlWr4saNGzA3N8eRI0eUjk1EREQqxMKaiIhMTm5uLgYNGoSsrCzcv38flStXxr59+4yf379/HzExMThz5gzS0tLQv39/eHh4sA2ciIiIfhcW1kREZJIuX76MESNGYP/+/fD19cWUKVPQrFkzpWMRERGRCWJhTUREJmvixIkoKChAeno6cnNz4evrixEjRsDMzAwAsH37drRq1QqVK1dWOCkRERGpGQtrIiIyOSICjUaDvLw8lCpVCgcOHMD69etx/vx5NGvWDIGBgUhLS4Ovry+ys7NRrlw5pSMTERGRirGwJiIik6HX66HVapGVlYXHjx/j8ePHcHV1BQDcvn0ba9asQWxsLNLS0lBQUIDw8HB8+umnCqcmIiIitWNhTUREJqGwsBDm5uY4e/YsJk6ciKSkJDRo0AB2dnaYN28e6tWrBwCIj49HTk4OzM3N0blzZ4VTExERkSlgYU1ERKpnaP0GABcXF3Tq1AlBQUHYtWsXQkNDUa1aNUyePBljxoxROCkRERGZIhbWRERkMiIiIrBz504cPXoUAFCnTh14eHhAq9Viw4YN8PHxwcKFC1GlShWFkxIREZEp0SodgIiI6G14+vQpnjx5gh49egAAxo4di8qVKyM6Ohpjx45FuXLlEBsbi02bNimclIiIiEyNudIBiIiI3gYrKyuEhobi0qVLyMvLw5kzZzBy5EgAQI0aNdChQwf4+vqiV69eCiclIiIiU8MZayIiMgl6vR6WlpaoV68eCgsLkZmZiYSEBADA4cOH8dNPP8HNzU3hlERERGSKOGNNRESqZVgmRKPRQKv931ixra0txowZgyVLluCHH35Afn4+RowYAUdHR6WiEhERkQnj4mVERKQ6//rXv1C9enXjFlqG/auLysrKQnx8PK5evYpKlSph4MCBSkQlIiKiEoCFNRERqUpmZib69OmDMmXKIDAwEH369AHw6uI6ISEBNWvWRKVKlZSISkRERCUE37EmIiJVcXBwwLhx42BnZ4dFixYhNDQUd+7cMRbVhvHixMRE9O7dG//5z3+UjEtEREQlAGesiYhIlS5evIjo6GgcOXIEVapUQWBgIDp37gwAePjwIbp3746yZctiz549CiclIiIiU8fCmoiIVEuv12PDhg3YsmULnjx5Am9vb4wePRqLFy/Gl19+iczMTFhYWCgdk4iIiEwcC2siIlK9U6dOITo6GikpKbC2tkZsbCxiYmLg6empdDQiIiIqAVhYExGRSXjy5AnWrVuHyMhI9O7dG+Hh4UpHIiIiohKChTUREZmU06dPw9XVVekYREREVIKwsCYiIiIiIiJ6A9xui4iIiIiIiOgNsLAmIiIiIiIiegMsrImIiIiIiIjeAAtrIiIiIiIiojfAwpqIiIiIiIjoDbCwJiIiIiIiInoDLKyJiIiIiIiI3gALayIiIiIiIqI3wMKaiIiIiIiI6A2wsCYiIiIiIiJ6AyysiYiIiIiIiN7A/wEVSYymYOMqdQAAAABJRU5ErkJggg==\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "Read this plot as the dominant effect size in the dataset: target choice swamps generator choice. Any model comparison that does not stratify by target is mostly measuring which targets that model was pointed at.\n", "\n", "==============================================================================\n", " 4. PER-PREDICTOR DISCRIMINATIVE POWER\n", "==============================================================================\n", "Predictors (10): af3of3, afm3, boltz2, chai1, ef2fast, ef2full, odde, of3, ptxv2, rf3\n", "\n", "AUC vs experimental binder_final:\n", "predictor metric auc lo hi n ap\n", " chai1 ipsae_min 0.744 0.711 0.777 1314 0.462\n", " of3 ipsae_min 0.741 0.714 0.767 1314 0.468\n", " afm3 ipsae_min 0.732 0.702 0.761 1224 0.454\n", " ef2full ipsae_min 0.720 0.691 0.747 1314 0.408\n", " ef2fast ipsae_min 0.719 0.691 0.747 1314 0.401\n", " af3of3 ipsae_min 0.709 0.679 0.737 1314 0.405\n", " odde ipsae_min 0.696 0.666 0.723 1314 0.391\n", " ptxv2 ipsae_min 0.692 0.661 0.722 1314 0.381\n", " boltz2 ipsae_min 0.692 0.665 0.721 1314 0.389\n", " rf3 ipsae_min 0.688 0.652 0.713 1314 0.413\n", " afm3 sc_dockq 0.688 0.654 0.717 1086 0.424\n", " boltz2 sc_dockq 0.681 0.647 0.713 1148 0.412\n", " of3 sc_dockq 0.678 0.645 0.710 1148 0.407\n", " chai1 sc_dockq 0.677 0.644 0.710 1148 0.403\n", " rf3 sc_dockq 0.656 0.622 0.689 1148 0.368\n", " ef2fast sc_dockq 0.655 0.621 0.688 1148 0.402\n", " af3of3 sc_dockq 0.654 0.619 0.689 1148 0.381\n", " odde sc_dockq 0.652 0.615 0.684 1148 0.385\n", " ef2full sc_dockq 0.630 0.594 0.665 1148 0.363\n", " ptxv2 sc_dockq 0.627 0.591 0.660 1148 0.367\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Interpretation: AUCs land well above chance but far below the ~0.9 you would need to trust a single filter. That gap is the entire practical reason this dataset exists.\n", "\n", "==============================================================================\n", " 5. CONSENSUS SCORING\n", "==============================================================================\n", "Best single column: ipsae_min_chai1 AUC=0.744\n", "\n", " cons_ipsae AUC=0.750 [0.722, 0.775] AP=0.463\n", " cons_dockq AUC=0.690 [0.658, 0.722] AP=0.425\n", " cons_all AUC=0.738 [0.709, 0.764] AP=0.450\n", " cons_median AUC=0.720 [0.692, 0.747] AP=0.423\n", " cons_min AUC=0.752 [0.726, 0.778] AP=0.487\n", " cons_disagree AUC=0.470 [0.436, 0.502] AP=0.252\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "If every off-diagonal cell were ~1.0 there would be no ensemble gain to harvest. The moderate correlations are why cons_all typically edges out the best single predictor — and why disagreement itself carries signal.\n", "\n", "==============================================================================\n", " 6. BUDGET CURVES (precision@N)\n", "==============================================================================\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Enrichment at small budgets:\n", " N= 25 | random 0.269 | best-single 0.160 (0.59x) | consensus 0.440 (1.63x)\n", " N= 50 | random 0.269 | best-single 0.360 (1.34x) | consensus 0.500 (1.86x)\n", " N= 100 | random 0.269 | best-single 0.520 (1.93x) | consensus 0.540 (2.00x)\n", " N= 200 | random 0.269 | best-single 0.510 (1.89x) | consensus 0.485 (1.80x)\n", "\n", "==============================================================================\n", " 7. VENDOR CONCORDANCE\n", "==============================================================================\n", "Designs with calls from BOTH vendors: 1,175\n", "\n", "twist_binding binder non_binder\n", "adaptyv_binding \n", "binder 253 69\n", "non_binder 56 797\n", "\n", "Raw agreement: 0.894 Cohen's kappa: 0.729\n", "Kappa well under 1.0 means part of the 'unpredictable' variance above is assay disagreement, not model failure.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Median KD ratio (Twist/Adaptyv): 0.55x -> systematic format offset, so treat absolute KD across vendors as ordinal, not interchangeable.\n", "\n", "==============================================================================\n", " 8. EXPRESSION CONFOUND\n", "==============================================================================\n", "Titer (mg/mL) binders median 0.86 (n=340) | non-binders 0.77 (n=914) Mann-Whitney p=1.75e-01\n", "AUC of raw expression titer alone as a 'binder' predictor: 0.525\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "Takeaway: if expression alone scores meaningfully above 0.5, then part of every AUC in section 4 is a solubility signal riding along. To isolate interface quality, re-run section 4 restricted to designs that expressed.\n", " consensus AUC, all evaluable : 0.738 (n=1314)\n", " consensus AUC, expressed only : 0.749 (n=1234)\n", "\n", "==============================================================================\n", " 9. EPITOPE CONVERGENCE\n", "==============================================================================\n", " target n_bind n_non J_binders J_nonbinders delta\n", " TNFa 12 138 0.703 0.318 0.385\n", " EGFR 10 80 0.470 0.336 0.135\n", " Nipah-G 19 71 0.293 0.201 0.092\n", " BHRF1 23 66 0.561 0.490 0.071\n", " TREM2 72 18 0.494 0.428 0.066\n", " IL-7Ra 49 41 0.475 0.415 0.060\n", " VEGF-A 54 36 0.408 0.377 0.031\n", " TrkA 20 70 0.417 0.410 0.007\n", "Latent GDF-8 14 41 0.290 0.291 -0.002\n", " PD-L1 39 51 0.529 0.559 -0.030\n", " BBF-14 3 87 0.216 0.256 -0.040\n", " Cas9 10 80 0.057 0.105 -0.049\n", " RBX1 28 62 0.410 0.464 -0.054\n", "\n", "Paired Wilcoxon across targets: p=0.1099 (binders more epitope-convergent than failures?)\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "==============================================================================\n", " 10. MODELLING WITH HONEST CROSS-VALIDATION\n", "==============================================================================\n", "feature set random 5-fold grouped-by-target\n", "------------------------------------------------------------------\n", "in-silico only 0.828 +/- 0.008 0.674 +/- 0.027\n", "sequence only 0.710 +/- 0.012 0.508 +/- 0.052\n", "in-silico + sequence 0.852 +/- 0.009 0.708 +/- 0.053\n", "\n", "Random-CV minus grouped-CV for the full feature set: +0.144\n", "That gap is leakage: features that encode target identity (epitope size, length priors, generator habits) let a randomly-split model recover the per-target base rate instead of learning what makes a binder. Report the grouped number; the random one is what a target-blind reviewer will catch.\n", "\n", "Control - target one-hot ONLY, random CV: AUC=0.807 (pure base-rate memorisation, zero design signal).\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "==============================================================================\n", " SUMMARY\n", "==============================================================================\n", "\n", " Evaluable designs : 1,314 base hit rate 0.269\n", " Best single in-silico : ipsae_min_chai1 AUC 0.744\n", " Rank-average consensus : AUC 0.738\n", " Honest ML (grouped CV) : AUC 0.708 <- the one to report\n", " Same model, random CV : AUC 0.852 (gap = +0.144 leakage)\n", "\n", " Five things this dataset teaches that a design paper usually cannot:\n", " 1. Target identity dominates every other factor; always stratify.\n", " 2. Structure-predictor confidence is real but weak signal (AUC ~0.6-0.75),\n", " nowhere near a standalone go/no-go filter.\n", " 3. Ensembling across predictors is a cheap, reliable few-points-of-AUC win.\n", " 4. Cross-vendor label noise caps how high any AUC here can honestly go.\n", " 5. Expression failure masquerades as binding failure. Condition on it.\n", "\n", " Extensions worth trying:\n", " - load_table('insilico_cofold_predictions') for all 5 seeds/predictor, and\n", " test whether seed VARIANCE beats seed-best as a confidence signal\n", " - load_table('adaptyv_fit_curves') to refit kinetics yourself and flag\n", " designs whose reported KD rests on a poorly-conditioned fit\n", " - load_table('insilico_provenance_steps') to relate optimisation-round count\n", " to eventual success\n", " - snapshot_download(..., allow_patterns='data/designs/EGFR//*') for\n", " mmCIF structures + PAE matrices on a single design\n", "\n" ] } ], "source": [ "head(10, \"MODELLING WITH HONEST CROSS-VALIDATION\")\n", "\n", "AAS = \"ACDEFGHIKLMNPQRSTVWY\"\n", "KD_HYDRO = dict(zip(AAS, [1.8, 2.5, -3.5, -3.5, 2.8, -0.4, -3.2, 4.5, -3.9, 3.8,\n", " 1.9, -3.5, -1.6, -3.5, -4.5, -0.8, -0.7, 4.2, -0.9, -1.3]))\n", "CHARGE = {\"K\": 1, \"R\": 1, \"H\": 0.1, \"D\": -1, \"E\": -1}\n", "\n", "def seq_features(seq):\n", " seq = \"\".join(ch for ch in str(seq).upper() if ch in AAS)\n", " L = max(1, len(seq))\n", " counts = {a: seq.count(a) / L for a in AAS}\n", " f = {f\"aa_{a}\": counts[a] for a in AAS}\n", " f[\"length\"] = len(seq)\n", " f[\"net_charge\"] = sum(CHARGE.get(c, 0) for c in seq)\n", " f[\"charge_density\"] = f[\"net_charge\"] / L\n", " f[\"gravy\"] = float(np.mean([KD_HYDRO[c] for c in seq])) if seq else 0.0\n", " f[\"aromatic\"] = sum(counts[a] for a in \"FWY\")\n", " f[\"helix_prone\"] = sum(counts[a] for a in \"AELM\")\n", " f[\"beta_prone\"] = sum(counts[a] for a in \"VIYFT\")\n", " f[\"gly_pro\"] = counts[\"G\"] + counts[\"P\"]\n", " p = np.array([counts[a] for a in AAS]); p = p[p > 0]\n", " f[\"entropy\"] = float(-(p * np.log2(p)).sum())\n", " run, best = 0, 0\n", " for c in seq:\n", " run = run + 1 if KD_HYDRO[c] > 1.5 else 0\n", " best = max(best, run)\n", " f[\"max_hydrophobic_run\"] = best\n", " return f\n", "\n", "SF = pd.DataFrame([seq_features(s) for s in ev.sequence], index=ev.index)\n", "seq_cols = list(SF.columns)\n", "sil_cols = [c for c in ev.columns if c.startswith((\"ipsae_min_\", \"sc_dockq_\"))] + \\\n", " [\"cons_all\", \"cons_min\", \"cons_disagree\"]\n", "meta_cols = [c for c in [\"rank\", \"n_optimization_rounds\", \"epitope_n_residues\"] if c in ev.columns]\n", "\n", "X_all = pd.concat([ev[sil_cols + meta_cols], SF], axis=1)\n", "y = ev.y.values\n", "groups = ev.target.values\n", "\n", "FEATURE_SETS = {\n", " \"in-silico only\": sil_cols + meta_cols,\n", " \"sequence only\": seq_cols,\n", " \"in-silico + sequence\": sil_cols + meta_cols + seq_cols,\n", "}\n", "\n", "def cv_auc(X, y, splitter, groups=None):\n", " aucs = []\n", " it = splitter.split(X, y, groups) if groups is not None else splitter.split(X, y)\n", " for tr, te in it:\n", " if len(np.unique(y[te])) < 2:\n", " continue\n", " m = HistGradientBoostingClassifier(max_depth=4, max_iter=250,\n", " learning_rate=0.06, random_state=SEED)\n", " m.fit(X.iloc[tr], y[tr])\n", " aucs.append(roc_auc_score(y[te], m.predict_proba(X.iloc[te])[:, 1]))\n", " return float(np.mean(aucs)), float(np.std(aucs)), len(aucs)\n", "\n", "print(f\"{'feature set':24s} {'random 5-fold':>18s} {'grouped-by-target':>20s}\")\n", "print(\"-\" * 66)\n", "results = {}\n", "for name, cols in FEATURE_SETS.items():\n", " X = X_all[cols]\n", " r_mean, r_sd, _ = cv_auc(X, y, StratifiedKFold(5, shuffle=True, random_state=SEED))\n", " g_mean, g_sd, nf = cv_auc(X, y, GroupKFold(n_splits=5), groups=groups)\n", " results[name] = (r_mean, g_mean)\n", " print(f\"{name:24s} {r_mean:.3f} +/- {r_sd:.3f} {g_mean:.3f} +/- {g_sd:.3f}\")\n", "\n", "gap = results[\"in-silico + sequence\"][0] - results[\"in-silico + sequence\"][1]\n", "print(f\"\\nRandom-CV minus grouped-CV for the full feature set: {gap:+.3f}\")\n", "print(\"That gap is leakage: features that encode target identity (epitope size, \"\n", " \"length priors, generator habits) let a randomly-split model recover the \"\n", " \"per-target base rate instead of learning what makes a binder. Report the \"\n", " \"grouped number; the random one is what a target-blind reviewer will catch.\")\n", "\n", "Xt = pd.get_dummies(pd.Series(groups, index=ev.index), prefix=\"tgt\")\n", "r_mean, _, _ = cv_auc(Xt, y, StratifiedKFold(5, shuffle=True, random_state=SEED))\n", "print(f\"\\nControl - target one-hot ONLY, random CV: AUC={r_mean:.3f} \"\n", " \"(pure base-rate memorisation, zero design signal).\")\n", "\n", "gkf = GroupKFold(n_splits=5)\n", "tr, te = next(iter(gkf.split(X_all, y, groups)))\n", "model = HistGradientBoostingClassifier(max_depth=4, max_iter=250,\n", " learning_rate=0.06, random_state=SEED).fit(\n", " X_all[FEATURE_SETS[\"in-silico + sequence\"]].iloc[tr], y[tr])\n", "imp = permutation_importance(model, X_all[FEATURE_SETS[\"in-silico + sequence\"]].iloc[te],\n", " y[te], n_repeats=12, random_state=SEED, scoring=\"roc_auc\")\n", "order = np.argsort(imp.importances_mean)[-18:]\n", "names = np.array(FEATURE_SETS[\"in-silico + sequence\"])[order]\n", "\n", "fig, ax = plt.subplots(figsize=(7, 5))\n", "ax.barh(names, imp.importances_mean[order],\n", " xerr=imp.importances_std[order], color=\"#55A868\")\n", "ax.set_xlabel(\"drop in AUC when permuted\")\n", "ax.set_title(\"Permutation importance (held-out target block)\")\n", "plt.tight_layout(); plt.show()\n", "\n", "head(\"\", \"SUMMARY\")\n", "print(f\"\"\"\n", " Evaluable designs : {len(ev):,} base hit rate {ev.y.mean():.3f}\n", " Best single in-silico : {best_col} AUC {best_single.auc:.3f}\n", " Rank-average consensus : AUC {auc_ci(ev.y, ev.cons_all)['auc']:.3f}\n", " Honest ML (grouped CV) : AUC {results['in-silico + sequence'][1]:.3f} <- the one to report\n", " Same model, random CV : AUC {results['in-silico + sequence'][0]:.3f} (gap = {gap:+.3f} leakage)\n", "\n", " Five things this dataset teaches that a design paper usually cannot:\n", " 1. Target identity dominates every other factor; always stratify.\n", " 2. Structure-predictor confidence is real but weak signal (AUC ~0.6-0.75),\n", " nowhere near a standalone go/no-go filter.\n", " 3. Ensembling across predictors is a cheap, reliable few-points-of-AUC win.\n", " 4. Cross-vendor label noise caps how high any AUC here can honestly go.\n", " 5. Expression failure masquerades as binding failure. Condition on it.\n", "\n", " Extensions worth trying:\n", " - load_table('insilico_cofold_predictions') for all 5 seeds/predictor, and\n", " test whether seed VARIANCE beats seed-best as a confidence signal\n", " - load_table('adaptyv_fit_curves') to refit kinetics yourself and flag\n", " designs whose reported KD rests on a poorly-conditioned fit\n", " - load_table('insilico_provenance_steps') to relate optimisation-round count\n", " to eventual success\n", " - snapshot_download(..., allow_patterns='data/designs/EGFR//*') for\n", " mmCIF structures + PAE matrices on a single design\n", "\"\"\")" ] } ] }