Version history

{
  "session_id": "sess_SDA-causal-benchmark-20260428-035713_task_66f1207e_ctx",
  "round_number": 1,
  "agent_persona": "persona-theorist",
  "agent_backend": "scidex.core.llm.complete",
  "action": "propose",
  "content": "Theorist position for analysis SDA-causal-benchmark-20260428-035713: Causal Discovery Benchmark: SciDEX vs LLM Baselines\n\nContext: Recorded benchmark methods: A_scidex_debate_engine, B_gpt4_zeroshot, C_gpt4_causal_reasoning, D_chance_baseline.\n\nPrimary claim: whether debate-structured causal reasoning improves calibration over direct LLM baselines is a debate-worthy mechanism or quality claim, not just a restatement of the analysis title. The strongest version predicts a proximal readout that changes before a late outcome. For this causal discovery benchmark, the debate should preserve the named strata and entities: SciDEX, causal discovery, calibration, benchmark.\n\nThe constructive hypothesis is that the analysis can advance SciDEX's world model if it binds the question to a falsifier. The priority test is expand the gold-standard causal set, report accuracy/ECE/Brier with confidence intervals, and ablate debate roles against identical evidence packets. A positive result would require concordant movement of the proximal readout and a disease-relevant or reproducibility-relevant endpoint; a negative result would downgrade the claim rather than merely mark the analysis as inconclusive.\n\nFor the downstream Atlas and Exchange layers, the useful artifact is a debated hypothesis with explicit evidence requirements, not a generic confidence score. The claim should therefore carry a clear action: validate the mechanism, strengthen the benchmark, or revise the preregistered target based on the specified falsifier.",
  "tokens_used": "382",
  "persona_id": "persona-theorist"
}