#000037 §22 Finding 3: per-audit-mode τ_qa in dry-run
Per Finding 3, a uniform τ_qa=7d filtered out every recent CANONICAL_PROJECTION row (the π* graduations from #000027/#000030/ #000032 are all younger than 7d), so the sweep saw zero high-value kernel-only work. Splitting τ_qa by audit_mode lets the cheap kernel re-probe path (CP) run on a short cycle while the expensive LLM re-witness path (STRICT/HYBRID/UNGROUNDED) keeps the long cycle. bench/scripts/prometheus_sigma_sweep_dryrun.py: new build_tau_by_mode() helper + per-mode CASE in iter_target_a_candidates; sweep_target_a now takes the dict instead of a single seconds value. New CLI flag --tau-qa-cp-days (default 1d); --tau-qa-days now scopes to LLM-witness modes only (default 7d). Report renders the per-mode τ table in the header and marks Findings 2 and 3 RESOLVED with their landing commits. Makefile: PROMETHEUS_SWEEP_TAU_DAYS bumped to 7 (was 1, the prior Finding-3 workaround); new PROMETHEUS_SWEEP_TAU_CP_DAYS=1 makevar. bench/results/prometheus-sigma-sweep-dryrun-2026-05-10.md: regenerated under the new defaults — 9 CP rows surface alongside 1,904 LLM- witness candidates → 1,913 total Target A candidates → 1 ACCEPT, 2 MARGINAL, 205 REJECT, 271 DEFERRED chunks; 2 cache_drift vetoes preserved end-to-end. docs/tickets/ticket-000037 §22: Findings 2 + 3 marked RESOLVED with landing-commit references; total dry-run cost line updated to the new measurements (37.6 ms / 3,913 branches / 9.6 µs per branch).
This commit is contained in:
parent
43380b11b7
commit
1f882df22c
4 changed files with 174 additions and 87 deletions
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@ -71,11 +71,31 @@ from arborist.substrate.prometheus import (
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DEFAULT_SHARDS_DIR = Path.home() / ".arborist" / "shards"
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DEFAULT_TAU_QA_DAYS = 7
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DEFAULT_TAU_QA_DAYS = 7 # LLM-witness modes (STRICT / HYBRID / UNGROUNDED)
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DEFAULT_TAU_QA_CP_DAYS = 1 # kernel-only mode (CANONICAL_PROJECTION)
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DEFAULT_TARGET_B_SAMPLE_PER_SHARD = 1000
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DEFAULT_BUDGET = 4 # Hermes concurrent-request ceiling (§11)
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def build_tau_by_mode(
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cp_days: int = DEFAULT_TAU_QA_CP_DAYS,
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llm_days: int = DEFAULT_TAU_QA_DAYS,
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) -> dict[str, int]:
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"""Per §22 Finding 3 (RESOLVED): split τ_qa by audit_mode.
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Kernel-only modes (CANONICAL_PROJECTION) take a short τ — cheap
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to re-probe, high value when kernel-LLM divergence surfaces.
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LLM-witness modes (STRICT / HYBRID / UNGROUNDED) take a longer τ
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— re-witness is expensive. Returns seconds per mode.
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"""
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return {
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"CANONICAL_PROJECTION": cp_days * 86400,
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"STRICT": llm_days * 86400,
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"HYBRID": llm_days * 86400,
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"UNGROUNDED": llm_days * 86400,
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}
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# ---------------------------------------------------------------------
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# Target A — providence_cache classification + synthesis
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# ---------------------------------------------------------------------
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@ -90,18 +110,31 @@ AUDIT_MODE_TO_DELTA_5F: dict[str, float] = {
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def iter_target_a_candidates(
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conn: sqlite3.Connection, tau_qa_seconds: int, now: int
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conn: sqlite3.Connection, tau_by_mode: dict[str, int], now: int
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) -> Iterator[sqlite3.Row]:
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"""Enumerate providence_cache rows older than τ_qa."""
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"""Enumerate providence_cache rows older than per-mode τ_qa.
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``tau_by_mode`` maps audit_mode → seconds; rows whose audit_mode
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is absent from the dict fall through to ``fallback_seconds`` (the
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longest declared τ — never filter MORE aggressively than declared).
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See :func:`build_tau_by_mode` for the §22 Finding 3 rationale.
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"""
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conn.row_factory = sqlite3.Row
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cur = conn.execute(
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fallback_seconds = max(tau_by_mode.values(), default=7 * 86400)
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case_clauses: list[str] = []
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case_params: list[int] = []
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for mode in sorted(tau_by_mode):
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case_clauses.append(f"WHEN audit_mode = '{mode}' THEN ?")
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case_params.append(tau_by_mode[mode])
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sql = (
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"SELECT cache_key, audit_mode, falsification_state, n_quotes,"
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" n_verified, unverified_quotes, hit_count, created_at,"
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" question_text"
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" FROM providence_cache"
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" WHERE ? - created_at >= ?",
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(now, tau_qa_seconds),
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f" WHERE ? - created_at >= (CASE {' '.join(case_clauses)}"
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f" ELSE ? END)"
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)
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cur = conn.execute(sql, [now, *case_params, fallback_seconds])
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yield from cur
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@ -290,7 +323,12 @@ def target_b_branch(
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# ---------------------------------------------------------------------
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def sweep_target_a(shards_dir: Path, tau_qa_seconds: int, now: int, chunk_size: int = 4) -> dict:
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def sweep_target_a(
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shards_dir: Path,
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tau_by_mode: dict[str, int],
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now: int,
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chunk_size: int = 4,
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) -> dict:
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"""Iterate Target A candidates across all shards; controller-decide per chunk.
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Default chunk_size = 4 mirrors the Hermes concurrency budget (§11)
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@ -335,7 +373,7 @@ def sweep_target_a(shards_dir: Path, tau_qa_seconds: int, now: int, chunk_size:
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continue
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batch: list[ControllerBranch] = []
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for row in iter_target_a_candidates(conn, tau_qa_seconds, now):
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for row in iter_target_a_candidates(conn, tau_by_mode, now):
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candidates_total += 1
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audit_mode_seen[(row["audit_mode"] or "UNKNOWN").upper()] += 1
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batch.append(target_a_branch(row))
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@ -526,8 +564,9 @@ def render_markdown(a_results: dict, b_results: dict, opts: dict) -> str:
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lines.append("## Parameters")
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lines.append("")
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lines.append(f"- Shards dir: `{opts['shards_dir']}`")
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lines.append(f"- τ_qa: {opts['tau_qa_days']} days "
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f"({opts['tau_qa_seconds']} seconds)")
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lines.append(f"- τ_qa per audit_mode (§22 Finding 3 fix):")
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for mode, secs in sorted(opts["tau_by_mode"].items()):
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lines.append(f" - {mode}: {secs // 86400}d ({secs}s)")
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lines.append(f"- Target B sample/shard: {opts['sample_b']}")
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lines.append(f"- Controller budget (Hermes concurrency): "
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f"{DEFAULT_BUDGET}")
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@ -681,31 +720,39 @@ def render_markdown(a_results: dict, b_results: dict, opts: dict) -> str:
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)
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lines.append("")
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lines.append(
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"**Finding 2 — flat capital_cost = no allocation.** "
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"Iteration 1 also assigned `capital_cost=1.0` to every "
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"branch (one full Hermes call). Combined with small "
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"audit-mode-based Δ5F deltas (±0.05–0.10), every utility "
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"was negative. Split kernel-only re-probe cost from full "
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"LLM-witness cost: `CANONICAL_PROJECTION=0.05`, "
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"`UNGROUNDED=0.4`, `HYBRID=0.8`, `STRICT=1.0` for Target A; "
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"`0.02` (HEAD-only freshness) vs `0.05` (canonical-shape "
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"probe) for Target B. Recommendation for Phase 3: model "
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"`capital_cost` as the expected cost given which witness "
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"paths fire (kernel / lexical / LLM), not a flat per-call "
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"estimate."
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"**Finding 2 — flat capital_cost = no allocation. "
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"RESOLVED in Phase 1.c (commit `4b85a0a`).** "
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"Iteration 1 assigned `capital_cost=1.0` to every branch "
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"(one full Hermes call). Combined with small audit-mode-"
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"based Δ5F deltas (±0.05–0.10), every utility was "
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"negative. The dry-run since splits kernel-only re-probe "
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"cost from full LLM-witness cost: "
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"`CANONICAL_PROJECTION=0.05`, `UNGROUNDED=0.4`, "
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"`HYBRID=0.8`, `STRICT=1.0` for Target A; `0.02` "
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"(HEAD-only freshness) vs `0.05` (canonical-shape probe) "
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"for Target B. Phase 1.c then promoted the split into the "
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"controller's input contract — `ControllerBranch` now "
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"exposes `kernel_cost` + `llm_cost` fields and a "
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"back-compat `effective_cost` property (legacy "
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"`capital_cost` callers continue to work)."
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)
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lines.append("")
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lines.append(
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"**Finding 3 — τ_qa=7d filters out every "
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"CANONICAL_PROJECTION row.** All 29 CP rows in `qa.db` are "
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"≤ 7 days old (they're the recent π* graduations from "
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"tickets #000027/#000030/#000032). Sweep with τ_qa=7d "
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"shows zero CP candidates → zero ACCEPT chunks → zero "
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"high-value sleep work surfaced. Phase 3 should split τ "
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"by audit_mode: kernel-only modes (CP) get τ_qa=1d (cheap "
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"to re-probe, high value when kernel-LLM divergence "
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"surfaces); lexical/quote modes (STRICT/HYBRID/UNGROUNDED) "
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"stay at τ_qa=7d (expensive LLM calls)."
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"CANONICAL_PROJECTION row. RESOLVED in this dry-run "
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"iteration.** All 29 CP rows in `qa.db` were ≤ 7 days old "
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"(they're the recent π* graduations from tickets "
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"#000027/#000030/#000032); a uniform τ_qa=7d returned zero "
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"CP candidates → zero ACCEPT chunks → zero high-value "
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"sleep work surfaced. The dry-run now splits τ by "
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"audit_mode via `build_tau_by_mode()` + per-mode `CASE` "
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"in `iter_target_a_candidates`: kernel-only modes (CP) "
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"default to τ_qa=1d (cheap to re-probe, high value when "
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"kernel-LLM divergence surfaces); LLM-witness modes "
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"(STRICT/HYBRID/UNGROUNDED) stay at τ_qa=7d (expensive "
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"LLM calls). Tunable via `--tau-qa-cp-days` + "
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"`--tau-qa-days` CLI flags. Phase 3 lifts both into "
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"governance parameters."
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)
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lines.append("")
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lines.append(
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@ -734,20 +781,24 @@ def render_markdown(a_results: dict, b_results: dict, opts: dict) -> str:
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)
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lines.append("")
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lines.append(
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"1. Per-audit-mode τ + per-audit-mode cost class (split "
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"kernel-cost from LLM-cost on the input contract — "
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"consider adding `kernel_cost` + `llm_cost` fields to "
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"`ControllerBranch` in a v2 dataclass)."
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"1. ~~Per-audit-mode τ + per-audit-mode cost class.~~ "
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"**Landed.** Cost-class split landed in Phase 1.c (commit "
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"`4b85a0a`); per-audit-mode τ landed in this dry-run "
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"iteration. Phase 3 promotes both into governance "
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"parameters (cache-key hash inputs)."
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)
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lines.append(
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"2. Chunk size = Hermes concurrency (4 today, governance "
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"param going forward)."
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)
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lines.append(
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"3. Sweep-specific weight profile (gamma_5f bumped, "
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"lambda_capital_cost dropped) since sweep work is "
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"deliberately accepting capital cost in exchange for "
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"falsification discovery."
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"3. ~~Sweep-specific weight profile (gamma_5f bumped, "
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"lambda_capital_cost dropped).~~ **Landed in Phase 1.c "
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"(commit `4b85a0a`)** — `arborist.substrate.prometheus."
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"sweep_weights()` returns the tuned profile "
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"(gamma_5f=1.5, lambda_capital_cost=0.25, "
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"nu_witness_divergence=0.5). Phase 3's scheduler picks it "
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"up via `WEIGHT_PROFILES['sweep']`."
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)
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lines.append(
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"4. MARGINAL queue from Target B becomes the funnel for "
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@ -783,7 +834,13 @@ def main(argv: list[str] | None = None) -> int:
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"--tau-qa-days",
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type=int,
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default=DEFAULT_TAU_QA_DAYS,
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help="re-witness providence_cache rows older than this many days",
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help="τ_qa for LLM-witness modes (STRICT/HYBRID/UNGROUNDED), days",
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)
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p.add_argument(
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"--tau-qa-cp-days",
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type=int,
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default=DEFAULT_TAU_QA_CP_DAYS,
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help="τ_qa for kernel-only mode (CANONICAL_PROJECTION), days",
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)
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p.add_argument(
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"--sample-b",
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@ -809,10 +866,12 @@ def main(argv: list[str] | None = None) -> int:
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return 1
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now = int(time.time())
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tau_qa_seconds = args.tau_qa_days * 86400
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tau_by_mode = build_tau_by_mode(
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cp_days=args.tau_qa_cp_days, llm_days=args.tau_qa_days
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)
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sys.stderr.write(f"Target A sweep over {args.shards_dir}...\n")
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a_results = sweep_target_a(args.shards_dir, tau_qa_seconds, now)
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a_results = sweep_target_a(args.shards_dir, tau_by_mode, now)
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sys.stderr.write(
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f" {a_results['candidates_total']} candidates, "
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f"{a_results['chunks_total']} chunks, "
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@ -833,7 +892,8 @@ def main(argv: list[str] | None = None) -> int:
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),
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"shards_dir": str(args.shards_dir),
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"tau_qa_days": args.tau_qa_days,
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"tau_qa_seconds": tau_qa_seconds,
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"tau_qa_cp_days": args.tau_qa_cp_days,
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"tau_by_mode": tau_by_mode,
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"sample_b": args.sample_b,
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}
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