feat(swarm): tiered A/B/C stock-opinions tier + gate-19 winner (rubric v15)
- run_tiered_swarm.py: variants A (flat reference), B (tiered: N deep-dive x6
roles 2-round+gossip + screen 1-round no-gossip, 6000-agent budget), C (pure
screen 5143 one-per-company), plus bias-control runs; deterministic tier
assignment (top market-cap + prior-run promotion flags), promotion file,
per-company consensus tie-break (confidence then agent_id), adversarial
peer routing, opinion schema score 0-10 / confidence 0-1.
- winner.py: gate-19 winner function — calibration (g13/g20), tiered-quality
(g18 beat baseline, g21 discrimination r cross-tier no-averaging-confound),
pick B if it proves quality else C, A never ships.
- adversarial_router.py: opposite-view routing (g14) + plain reinforcing router.
- bias_control.py: synthetic neutral dossiers + McNemar symmetry (g13).
- sql/dossier_screen.sql (8-quarter trend) and dossier_deepdive.sql (strict
superset + top holders + ownership trend) + contract tests.
- 60 tests pass (dry-run machinery end-to-end; live run is a named checkpoint).
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