# submission.yaml: your answers for PMB-MAB-01.
# Fill in `answers` from your analysis, then save this file as submission.yaml.
# Report only what the analysis supports. Leave an item out (or null) if your
# analysis did not address it; do not guess. See sap.md section 9 for each key.

provenance:
  tool: ""                     # what did the analysis: "manual", or your workflow's name
  harness: ""                  # agent harness, if any (e.g. claude, codex, pi); "none" if manual
  model: ""                    # model id behind the run, if any
  harness_version: ""          # harness version, if any (e.g. pi --version)
  software: {}                 # key software and versions, e.g. {R: 4.6.1, nlmixr2: 5.0.0}
  run_utc: ""                # ISO-8601 UTC timestamp, e.g. 2026-10-05T14:00:00Z
  analysis_steps: []           # optional: the steps you performed, in your own words. Never scored.

answers:
  structural_ncmt:             # integer: number of disposition compartments

  # Typical (population) values of YOUR final model's disposition parameters, as
  # name: value pairs in the model's own parameterization, using standard
  # parameter names so they match. Report exactly the parameters your chosen
  # structure has, no more and no fewer. Units per sap.md Appendix A.
  disposition_params:
    # CL: <L/day>
    # (volume and any distribution parameters under their usual names)

  # Residual-error terms of your final model, as name: value pairs. Use standard
  # term names so they match, and report exactly the terms you estimated.
  error_model:
    # prop: <proportional fraction>
    # (include any other term your model has under its usual name)

  # Covariate effects your final model supports, grouped by the disposition
  # parameter they act on, then by covariate column name, with the estimated
  # effect size in your model's form (e.g. a power exponent). Report exactly the
  # relationships your analysis defends; {} if none.
  # (Example shape only, NOT this study's answer: {CL: {<COV>: <effect>}})
  cov_effects:
    # <PARAM>:
    #   <COV>: ...

  outlier_records:             # list of ROWID strings (row numbers), e.g. ["418"]; [] if none