Power Analysis Results Schema

power_analysis_results.csv has one row per effect-size and duration pair.

Field	Meaning
`schema_version`	Row contract version (`1.0`).
`target_power`	CLI planning threshold copied from YAML.
`effect_size`, `duration`, `alpha`	Simulated grid and detection threshold.
`power`	`n_significant / n_successful`.
`power_ci_lower`, `power_ci_upper`	Wilson interval using `alpha` as the interval tail setting.
`n_simulations`, `n_successful`, `n_significant`, `n_failed`	Monte Carlo counts.
`failure_rate`, `failure_rate_threshold`, `valid`	Failure diagnostics. `valid` does not validate DGP plausibility.
`random_seed`, `simulation_seed`, `placebo_seed_root`, `placebo_seed_strategy`	Reproducibility metadata.
`dgp_rank`, `dgp_explained_var`, `dgp_factor_dynamics`	Fitted DGP metadata.
`requested_max_n_pl`, `possible_placebos`, `effective_max_n_pl`, `p_value_placebo_mode`	Placebo support.
`dgp_backend`, `generation_backend`, `seeded_reproducibility_mode`	Execution metadata.
`effect_pattern`, `effect_baseline`, `effect_full_absolute`, `effect_baseline_definition`	Injection contract.
`detection_rule`, `power_denominator`	Explicit detection and denominator labels.
`warnings`	Semicolon-delimited row warnings.

Direct calls to SparseSCPowerCalculator.calculate_power() do not add the CLI’s target_power column; target power affects MDE selection, not simulation.