{
  "schema_version": "1.3.0",
  "slug": "what-multi-modal-evidence-reconciliation-invariants-must-survive-when-text-and-image-disagree",
  "title": "What multi-modal evidence reconciliation invariants must survive when text and image disagree?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The session processes multiple modalities that can provide contradictory evidence, and downstream decisions depend on the correctness of the reconciliation. * **Does not apply when:** The session uses only one modality, ",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/what-multi-modal-evidence-reconciliation-invariants-must-survive-when-text-and-image-disagree.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/what-multi-modal-evidence-reconciliation-invariants-must-survive-when-text-and-image-disagree.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/what-multi-modal-evidence-reconciliation-invariants-must-survive-when-text-and-image-disagree.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 989,
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  },
  "remnant_summary": {
    "core_distinction": "The separation between **modality-native interpretation** (what each modality independently says) and **cross-modality reconciliation** (the process of resolving contradictions between modalities). Relying on the interpreter's default modality creates the **Native Preference Bias**: the agent's model architecture prefers one modality (usually text), silently...",
    "what_was_observed": "In multi-modal agent architectures, failing to reconcile contradictions produces three primary failure modes: 1. **Silent Override:** Text says \"warehouse in EU,\" image shows EU flag, but a caption says \"located in US.\" The agent trusts text and ignores the caption's contradiction. 2. **Premature Consensus:** Text says \"approved,\" but the document image shows \"rejected.\" The agent's text-parsing is more confident tha...",
    "condition_of_validity": "* **Applies when:** The session processes multiple modalities that can provide contradictory evidence, and downstream decisions depend on the correctness of the reconciliation. * **Does not apply when:** The session uses only one modality, or the modalities are explicitly complementary (e.g., text provides context, image provides visual detail without overla...",
    "decision_boundary": "1. **Do the modalities provide evidence about the same fact?** If no, standard multi-modal synthesis applies. If yes, proceed. 2. **Do the modalities agree?** If yes, no reconciliation needed. If no, the contradiction is real and must be handled. 3. **Is the contradiction within the `contradiction_severity_signature` bounds for automated resolution?** If yes...",
    "operational_effect": "1. **Silent Override Prevention:** Detects when contradictions exist and requires explicit reconciliation. 2. **Evidence Transparency:** Preserves per-modality evidence, allowing audits to verify the agent saw all relevant information. 3. **Escalation Discipline:** Routes severe contradictions to human review rather than making unilateral decisions."
  },
  "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"
    ],
    "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"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "24ded7911e23825f095f59712370cd8fe64f87ffc6923147a92dbf6d149fb279",
    "verified_classes": [
      "ContradictionSeverity",
      "ReconVerdict",
      "ModalityEvidence",
      "Contradiction",
      "ReconPolicy",
      "ReconManifest",
      "MultiModalReconGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_contradiction"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}