1# Treatment arms (CLAUDE.md §Deliberation protocols). Letters are canonical and used in tables.2arms:3 A_hedonic: {family: baseline, model: hedonic_ridge, note: "log-price OLS/ridge with municipality x quarter and grid fixed effects"}4 B_hierarchical: {family: baseline, model: hierarchical_hedonic, note: "mixed-effects hedonic with municipality and grid random intercepts; repeat-sales adjustment when the parcel has a prior sale"}5 C_gbm: {family: baseline, model: lightgbm, note: "LightGBM tuned on validation only; CatBoost/XGBoost reported as robustness"}6 D_avm: {family: baseline, model: avm, note: "GBM + comparable-based features + spatial-temporal lags + conformal / quantile intervals"}7 E_single_llm: {family: llm, roles: [generalist], rounds: 0}8 F_independent: {family: llm, roles: default12, rounds: 0, aggregation: all}9 G_debate: {family: llm, roles: default12, rounds: [1, 2, 4], protocol: structured_debate}10 H_debate_skeptic: {family: llm, roles: default12, rounds: 2, protocol: structured_debate, blinded_skeptic: true, evidence_verification: true}11 I_placebo: {family: llm, roles: shuffled12, rounds: 2, protocol: structured_debate, note: "role prompts randomly permuted / generic placeholder roles"}12 G_fullview: {family: llm, roles: default12_fullview, rounds: 2, protocol: structured_debate, note: "secondary contrast: default prompts, full packet for every role (value of the evidence partition)"}13 J_cost_matched: {family: llm, roles: [generalist], repeats: 12, rounds: 0, note: "single agent sampled k times to match the token budget of F/G; plus self-refine chain"}14aggregation_rules: [mean, median, trimmed_mean_20, inverse_variance, stacking, robust_bayes]15rounds_grid: [0, 1, 2, 4]16providers:17 committees: [all_anthropic, all_openai, mixed_random]18 tier: mid19