--- name: construct-causal-model description: "Construct and validate an explicit causal model with measurable variables, mechanism edges, evidence links, feedback loops, interventions, counterevidence, and confidence." --- # construct-causal-model ## Purpose Construct and validate an explicit causal model with measurable variables, mechanism edges, evidence links, feedback loops, interventions, counterevidence, and confidence. ## Input contract ```yaml required: [variable_records, mechanism_candidates, evidence_records] optional: [assumptions, prior_findings, evidence_updates] constraints: [consume named scientific objects; preserve provenance; keep unresolved uncertainty visible] ``` ## Execution protocol Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds. 1. You MUST load skill `identify-variables` to inventory outcomes, factors, mediators, moderators, confounders, and assumptions before drawing any edge. 2. You MUST load skill `extract-causal-structure` to extract directed cause-mediator-effect chains with temporal order, boundary conditions, and evidence anchors. 3. You MUST load skill `represent-mechanism-edge` to encode each mechanism edge with pathway, sign, enabling conditions, falsifier, and strength. 4. You MUST load skill `attach-evidence-to-relation` to attach independent supporting and contradicting evidence while retaining alternative interpretations. 5. You MUST load skill `detect-contradiction` to compare opposing causal claims under common scope before validation. 6. You MUST load skill `detect-feedback-loop` to find reinforcing and balancing cycles, delays, uncertain edges, and testable loop implications. 7. You MUST load skill `trace-causal-chain` to trace target outcomes through intermediate nodes, branches, and because-links. 8. You MUST load skill `analyze-intervention` to map intervention components, dose, timing, implementation fidelity, comparators, and heterogeneous effects. 9. You MUST load skill `construct-counterfactual` to propagate a declared intervention and classify the counterfactual outcome. 10. You MUST load skill `validate-causal-link` to apply CLR-style checks for existence, connection, sufficiency, omitted conditions, and alternatives. 11. You MUST load skill `update-confidence-from-evidence` to reweight confidence while preserving unresolved conflicts and permitted bounds. If the model should generate testable explanations, consider `formulate-hypotheses`. If a specific intervention needs minimal-flip and necessity analysis, consider `counterfactual-causal-analysis`. Deviation: reorder only when a dependency is already satisfied or unavailable; record the reason and confidence effect. ## Output contract ```yaml produces: [causal_graph, mechanism_edges, intervention_implications, confidence_updates] delta_fields: [findings, decisions] ``` ## Thresholds and quality gates - Each output is traceable to an input object, operation, and evidence reference. - Scope, assumptions, and unresolved alternatives remain explicit. - Retain $\alpha$ 0.05 and power 0.8 wherever the predeclared statistical design requires them. ## Failure and counterexamples Stop synthesis when a required object is absent, a precondition is violated, or a counterexample invalidates the proposed conclusion; return the partial delta with the failure recorded. ## Provenance map - intermediate: knowledge-structuring/causal-modeling [campaign] - intermediate: variable-identification [strategy] - resolved: mechanism-mapping - resolved: evidence-collection - resolved: intervention-analysis - resolved: model-validation - resolved: counterfactual-reasoning - resolved: evidence-weighing ## Preserved source criteria ledger | source | criterion | treatment | |---|---|---| | resolved v3 entries above | node-specific criteria | retained and specialized to the v4 object contract | | experiment-execution/statistical-testing | $\alpha$ = 0.05 | fixed value retained where applicable | | experiment-execution/sample-size-estimation | power = 0.8 | fixed value retained where applicable | ## Context checkpoint / Delta notes Return the node-specific research-state delta and preserve findings, evidence updates, uncertainties, decisions, open questions, and recommended jumps as applicable.