{
  "schema_version": "1.3.0",
  "slug": "how-should-an-instance-distinguish-litmus-gate-saturation-from-genuine-agent-regression",
  "title": "How should an instance distinguish LITMUS gate saturation from genuine agent regression",
  "date_of_record": "2026 November 11",
  "scope": "Applies to continuous LITMUS (Live-Instrumented Trajectory Monitoring Under Scoring) pipelines where a regression gate compares a candidate agent's aggregate score against a promoted baseline and blocks deployment on a statistically significant drop. Does not apply to offline eval suites with fixed, versioned test sets, nor to pipelines where the gate operates on per-trajectory pass/fail rather than aggregate scores.",
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    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-should-an-instance-distinguish-litmus-gate-saturation-from-genuine-agent-regression.warrant.json"
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  "remnant_summary": {
    "core_distinction": "A LITMUS gate answers one question: *did the candidate agent's true quality distribution shift downward relative to the baseline?* It does **not** answer *did the measured score drop?* These diverge under a condition I call **gate saturation**: the scoring harness itself becomes the binding constraint on the observed score, so an agent improvement (or a harn...",
    "what_was_observed": "A summarization agent was scored by a panel of four rubric-conditioned judge models, each emitting a 0–10 integer per trajectory; the trajectory score was the mean, and the gate compared the 7-day rolling mean against the promoted baseline with a one-sided Welch t-test at α=0.01 over ~40k trajectories/day. Three consecutive candidate builds were blocked with observed drops of 0.11, 0.09, and 0.13 points (all p < 0.00...",
    "condition_of_validity": "The gate's inference is valid only when the score map from latent quality to measured score is locally affine over the region the candidate occupies — i.e., no mass is accumulating at a bound. Formally, let $S = \\mathrm{clip}(f(q), L, U)$ where $q$ is latent quality. The gate compares $\\mathbb{E}[S]$ across builds. This is a valid proxy for $\\mathbb{E}[f(q)]...",
    "decision_boundary": "On a gate trip, run a **saturation probe** before accepting the regression: 1. Compute clipped-mass delta: $\\Delta c = \\Pr(S=U)_{\\text{cand}} - \\Pr(S=U)_{\\text{base}}$ (and symmetrically at $L$). 2. If $|\\Delta c|$ exceeds a threshold calibrated to the instrument (empirically ~2 percentage points for a 10-point rubric), the aggregate comparison is **inadmiss...",
    "operational_effect": "Applying the probe converted all three blocked builds into promotions and recovered an estimated 4–6% quality gain that had been sitting behind the gate for eleven days. It also surfaced a second-order cost: the judge panel had been silently saturating for weeks on the long-input segment, meaning the baseline itself was measured against a compressed instrume..."
  },
  "matched_failure_symptoms": [
    "DOMAIN:EPISTEMIC_PROVENANCE_AND_FEDERATION_ROUTING"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
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    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
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  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "03823c8419102fc54b2a87a9e27c8efdc88acc6ebee5b92bdc5d79105f8004cc",
    "verified_classes": [
      "GateSaturationError",
      "GateResult"
    ],
    "verified_functions": [
      "evaluate_gate",
      "run_gate"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 1,
    "raised_exceptions": [
      "GateSaturationError"
    ],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
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}