docs(confidence-engine): record matched provider reconstruction evidence
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@@ -1755,6 +1755,110 @@ The initial decomposition represents core factual uncertainty channels (normalis
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## v0.61.3 — Matched Provider Reconstruction Evidence Checkpoint
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**Status: DOCUMENTATION-ONLY CHECKPOINT**
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**Purpose:** Record six matched reconstruction-comparison observations (Qwen + Terra) against the canonical manufacturing fixture before moving downstream. No live model calls. No production changes.
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### Fixture under observation
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```
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tests/fixtures/manufacturing-complaints-scenario.json
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```
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Identical across all runs.
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### Production prompt / schema frozen
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- **Prompt:** `reconstruct-v0.5` (production default)
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- **Rule:** Rule 5a
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- **Salience check:** semantic-preservation
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- **Schema:** canonical reconstruction schema
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- **Path:** reconstruction-only experiment path
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### Qwen / Ollama evidence (3 matched observations)
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| Channel | Finding |
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|---|---|
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| A — complaints +35%, production +40%, complaint-rate-per-unit uncertainty | semantically stable |
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| B — CRM tagging / complaint-count comparability uncertainty | semantically stable |
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| C — late-delivery versus minor-product-defect distinction | meaning preserved, representation varied |
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| D1 — supplier-related defect uncertainty | meaning preserved, but supplier and shift frequently recombined |
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| D2 — weekend-shift-related defect uncertainty | meaning preserved, but supplier and shift frequently recombined |
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| E — intervention-fit dependency (whether £120k automated inspection is appropriate depends on understanding the actual quality problem) | core dependency preserved, graph topology varied |
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**Important observed pattern:** compound supplier/shift unknown appeared in all three Qwen runs.
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**Representation variance (Qwen):** late-delivery / defect graph granularity varied; supplier / weekend-shift node granularity varied; investment dependency topology varied; overall node count varied.
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**Wording of concern:** Qwen shows clear representation variance and a recurring semantic-compression tendency around independently investigable supplier/shift distinctions. This is documented as an observation, not yet classified as harmful or proven defective.
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### Terra / OpenAI evidence (3 matched observations)
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| Channel | Finding |
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|---|---|
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| A — complaints +35%, production +40% | stable |
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| B — CRM comparability | stable |
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| C — late-delivery vs defects | semantically stable and separately represented in all three |
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| D1 — supplier-related defect uncertainty | stable |
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| D2 — weekend-shift-related defect uncertainty | stable |
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| E — intervention-fit dependency | core dependency stable |
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**All three Terra runs:**
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| Check | Result |
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|---|---|
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| Supplier transition distinct | YES |
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| Weekend-shift transition distinct | YES |
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| Supplier unknown distinct | YES |
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| Weekend-shift unknown distinct | YES |
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| Compound supplier/shift unknown | NO |
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| Unsupported expansion | NO |
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| Causal strengthening | NO |
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**Structural/topological variance in Terra runs:** node counts varied; encoding between observedStates / differences / transitions varied; description granularity varied; E topology varied while preserving the dependency. Do not interpret this as deterministic graph output.
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### Cross-provider conclusion
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> Exact graph topology is not stable for either provider and should not be treated as a reconstruction invariant. The more important invariant is preservation and independent recoverability of supplied distinctions and uncertainties.
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> Terra showed stronger stability in preserving independently investigable C and D1/D2 distinctions as separate graph structures. Qwen preserved their meaning but more frequently compressed them into combined representations.
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**Not claimed:** provider superiority (sample too small, one fixture), prompt defect or fix, production provider migration decision.
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### Cost / development interpretation
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> Terra is currently useful as a paid reference/comparator. Qwen remains valuable as the low-cost/local development and potential runtime provider. The practical question is whether Qwen's semantic compression causes a downstream product consequence.
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No pricing assumptions or commercial projections added.
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### Next product boundary
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> **Does Qwen's recurring compression of independently investigable distinctions materially degrade the downstream Confidence Engine investigation flow?**
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Examples of downstream consequences to investigate later: an uncertainty becomes inaccessible as an Open Question; supplier and shift cannot be investigated independently; answer integration loses attribution; Current Understanding becomes less faithful; later graph updates cannot recover the original distinction.
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This experiment is **NOT** designed or run in this checkpoint task.
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### Live calls during this checkpoint
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- Qwen/Ollama: 0
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- Terra/OpenAI: 0
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- Application API: 0
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### Production / prompt / schema changed
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- Production code changed: NO
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- Prompt changed: NO
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- Schema changed: NO
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### Git
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**Commit message:** `docs(confidence-engine): record matched provider reconstruction evidence`
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---
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## v0.61 active restart point
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The current handoff direction is the repeated-same-input decomposition stability experiment described in the **active design** section at the top of §v0.61.
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