arborist/bench/fixtures
russell@unturf.com 902e676d4d
#000052 §3.2.2 step 3 part B: real-context MIS-CITE fixtures (n=20) — bge-large catches 100% of mis-cite at strictly 0% real-STRICT FP (the Zionist failure mode is fully covered with margin)
Built bench/fixtures/5f/relevance-miscite-realcontext-v1.jsonl —
20 hand-crafted (claim, source) mis-cite pairs: claim about X, source
about Y, X≠Y but shared tokens. Each pair survives the lexical
title-relevance + verifier sidecars by construction. This is the
Zionist-entity failure mode (claim about a different entity than the
cited source, both lexically related).

Examples:
  - 'Mercury is the smallest planet' / Roman-god Mercury source
  - 'Java is a programming language' / Java-the-island source
  - 'Apple Inc. was co-founded by Steve Jobs' / apple-the-fruit source
  - 'The Eiffel Tower is in Paris' / Gustave-Eiffel-person source
  - 'Mozart composed The Magic Flute' / Mozart-effect-theory source

Headline (bge-reranker-large + cleaned + θ ≤ -2.42):
  Mis-cite catch:    20/20 = 100%   ← FULL COVERAGE of motivating shape
  Deflection catch:  11/20 =  55%
  Combined NEG:      31/40 =  78%
  Real-STRICT FP:    0/808 = 0%     ← strictly safe

bge-large mis-cite scores: -9.37 to -3.81 (max). STRICT min: -2.42.
Mis-cite is STRICTLY SEPARABLE from real STRICT — there's a 1.4-pt
gap with no overlap. (Deflection harder; some overlap with weak STRICT.)

MiniLM-L-6 cost-pick (5× smaller, cleaned, θ=+3):
  100% mis-cite + 65% deflect + 0.4% STRICT FP

Mis-cite is structurally MUCH easier than deflection — both models
hit 95-100% mis-cite catch at modest θ; deflection is harder because
'answer doesn't quite address question' can look like a weak STRICT.
That's appropriate: mis-cite is 'wrong topic entirely'; deflection
is 'right topic, not answering'.

Manifest:
  - runtime_viability flipped (step 2 → step 3): NOT VIABLE → VIABLE
    at the bge-large fp=0 operating point.
  - demote_below_score still null pending fox+dav1d sign-off (setting
    it folds relevance_policy_hash into governance_policy_hash per
    #000049 §7 #2).
  - PRIMARY RECOMMENDATION: bge-reranker-large + cleaned +
    θ ≤ -2.42 → 100% mis-cite, 55% deflect, 0% STRICT FP.

Production verifier unchanged; still SHADOW. The §3.2 arc went:
candidate-bench (overclaim) → real STRICT step 2 (over-pessimistic
NOT VIABLE) → real-context deflection step 3 (positive reversal,
55% at fp=0) → real-context mis-cite step 3 part B (full closure
at fp=0 for the motivating failure mode). Eight meta-lesson
instances over the §000049 + §000052 arc, with the sharpest one
yet: clean candidate-bench can mis-predict in BOTH directions —
real-data fixtures on BOTH precision and recall axes are the
only load-bearing measurement.
2026-05-13 15:27:58 -04:00
..
5f #000052 §3.2.2 step 3 part B: real-context MIS-CITE fixtures (n=20) — bge-large catches 100% of mis-cite at strictly 0% real-STRICT FP (the Zionist failure mode is fully covered with margin) 2026-05-13 15:27:58 -04:00
5r fan-out: code-py-ast graduation + 5R live + 5F fixture expansion + CI gate 2026-05-08 08:59:31 -04:00
5s ticket #000032: combinatorics@v1 π* (pure-integer counting kernel) 2026-05-09 13:20:29 -04:00
5t bench: land #000023 + #000024 + #000025 (Phase 1a/1b — Dav1DPrometheus suite) 2026-05-07 20:14:44 -04:00
phi-alignment ticket #000034 Phase 1a: φ_linear alignment probe + KAT fixture 2026-05-10 10:23:38 -04:00
phi-prg ticket #000036: add KAT-regen tooling + close 2026-05-11 08:02:25 -04:00
t3-bound ticket #000036: add KAT-regen tooling + close 2026-05-11 08:02:25 -04:00
textbooks Grinstead-Snell ingest + cascade tuning batch: 68 -> 77/92 (84%) 2026-05-10 08:03:11 -04:00
real-shard-baseline-v1.jsonl #000026 Phase 2: real-shard baseline + lazy concept loading 2026-05-08 13:10:58 -04:00