confidence-engine/docs/archive/experiments/vol-1-chapters/ch19/initial-decomposition-v0.61.md

# Ch19 — Initial Decomposition Hardening (v0.61)

**Status: COMPLETE (frozen)**  
**Branch:** `feature/initial-decomposition-v0.61`  
**Final HEAD:** `5878ce4` experiment(confidence-engine): add reconstruction-only helper flag

## v0.61 Objective

How stable is the initial semantic decomposition of the same fixed scenario across repeated runs using the same model, prompt version and production API path?

## Fixed manufacturing scenario (used throughout)

```
I run a small manufacturing business. Customer complaints have risen by 35% over the last six months, while production volume increased by 40%.

Most complaints mention late delivery or minor product defects, but our complaint categories changed when we introduced a new CRM tagging system three months ago. During the same period we also changed one supplier and introduced a weekend production shift.

I am deciding whether to spend about £120,000 on automated quality inspection now or wait until we understand whether there is actually a quality problem.

I do not yet know the complaint rate per unit, whether defect rates differ by shift or supplier, or whether the new tagging system changed what gets counted as a complaint.
```

## v0.61.3 — Matched Provider Reconstruction Evidence Checkpoint

**Status:** DOCUMENTATION-ONLY CHECKPOINT  
**Purpose:** Record six matched reconstruction-comparison observations (Qwen + Terra) against the canonical manufacturing fixture before closing out. No live model calls. No production changes.

### Production prompt / schema frozen
- **Prompt:** `reconstruct-v0.5` (production default)
- **Rule:** Rule 5a
- **Salience check:** semantic-preservation
- **Schema:** canonical reconstruction schema
- **Path:** reconstruction-only experiment path

### Qwen / Ollama evidence (3 matched observations)

| Channel | Finding |
|---|---|
| A — complaints +35%, production +40%, complaint-rate-per-unit uncertainty | semantically stable |
| B — CRM tagging / complaint-count comparability uncertainty | semantically stable |
| C — late-delivery versus minor-product-defect distinction | meaning preserved, representation varied |
| D1 — supplier-related defect uncertainty | meaning preserved, but supplier and shift frequently recombined |
| D2 — weekend-shift-related defect uncertainty | meaning preserved, but supplier and shift frequently recombined |
| E — intervention-fit dependency | core dependency preserved, graph topology varied |

**Important observed pattern:** compound supplier/shift unknown appeared in all three Qwen runs.

### Terra / OpenAI evidence (3 matched observations)

| Channel | Finding |
|---|---|
| A — complaints +35%, production +40% | stable |
| B — CRM comparability | stable |
| C — late-delivery vs defects | semantically stable and separately represented in all three |
| D1 — supplier-related defect uncertainty | stable |
| D2 — weekend-shift-related defect uncertainty | stable |
| E — intervention-fit dependency | core dependency stable |

All three Terra runs: supplier transition distinct=YES, weekend-shift distinct=YES, compound supplier/shift=NO, unsupported expansion=NO, causal strengthening=NO.

### Cross-provider conclusion

> 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.

> 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.

## v0.61 Experiment 5 — Repeated Same-Input Initial Decomposition Stability

**Status:** INCOMPLETE — five runs required; obtained four successful plus one validation failure.

### Execution
- **Route:** POST /api/cases/start
- **Requests made:** 5 (4 successful, 1 validation failure)
- **Model:** `qwen-claude:latest`
- **Prompt version:** v0.2

### Structure Range

| | Nodes | Unknowns | Assumptions |
|---|---|---|---|
| Run 1 | 16 | 3 | 3 |
| Run 2 | 20 | 7 | 2 |
| Run 3 | 21 | 3 | 3 |
| Run 4 | 14 | 3 | 2 |

Unknown count: 3–7. Assumption count: 2–3. Total node count: 14–21.

### Semantic Channel Frequency (Runs 1–4)

```
A Normalisation:          4/4 present, 0/4 partial, 0/4 absent
B CRM comparability:      4/4 present, 0/4 partial, 0/4 absent
C Delivery vs defects:    1/4 present,   3/4 partial,  0/4 absent
D Supplier/shift/source:  4/4 present, 0/4 partial, 0/4 absent
E Intervention fit:       1/4 present,   0/4 partial,  3/4 absent
```

### Key findings

- Run 2 introduced speculative subdivisions not grounded in source text (customer segment variation, QC team capability shifts, responsibility distribution impact, batch-size/equipment utilization correlation).
- No run contained steering language, unsupported causal claims, premature arithmetic conclusions, or action recommendations.
- The £120k intervention was represented neutrally in all runs.

### Conclusion

Initial decomposition represents core factual uncertainty channels (normalisation, CRM comparability, supplier/shift ambiguity) to varying degrees. Primary instability: intervention-fit mapping and speculative subdivision risk. Graph topology varies materially (14–21 nodes).

## Focused-deconstruction plumbing fix (historical)

**Root cause:** focused route passed full provider envelope `{ response, providerApiPath, providerExecution }` into `validateFocusedDeconstructSchema()`. Validator expected semantic fields at top level but they lived on `wrapper.response`, not the wrapper. All six fields appeared absent → structured-output 502.

**Fix:** Route extracts `const deconstruction = wrapper.response` and passes inner object to validation and serialization. Provider diagnostics preserved but do not interfere with semantic fields.

**Tests:** `tests/focused-deconstruct-boundary.test.js` — 48 focused-investigation-boundary tests pass on first run. Previous two pre-fix semantic runs remain invalid as semantic evidence.

### Post-fix repeatability (3 controlled Qwen/Ollama runs)

| Metric | Result |
|---|---|
| Qwen/Ollama calls | 3 |
| HTTP 200 | 3/3 |
| schema valid | 3/3 |
| supplier evidence preservation | 3/3 PASS |
| weekend-shift uncertainty preservation | 3/3 PASS |
| epistemic separation | 3/3 PASS |
| unsupported inference | 0/3 |
| steering | 0/3 |

**Product interpretation:** For the fixed compound supplier/weekend-shift case, Qwen's initial compression did not prevent focused-investigation stage from repeatedly recovering the epistemic distinction once substantive user evidence was supplied. This supports tolerating some initial representation compression when meaning survives downstream.

This is **not yet generalised to a production invariant.**

## v0.61 — Closed experiment boundaries

| Boundary | Status |
|---|---|
| Repeated-same-input decomposition experiments | FROZEN |
| Qwen/Terra reconstruction comparison | FROZEN |
| Initial prompt refinement | FROZEN |
| Supplier/weekend-shift decomposition experiments | FROZEN |
| Relationship-preservation experiments | FROZEN |
| Causal-fidelity experiments | FROZEN |

## v0.4 initial reconstruction — implementation status

**Status:** COMPLETE — deterministic tests pass, one live smoke accepted  
**Prompt:** `prompts/reconstruct-v0.4.md` (replaced by v0.5 in production default)  
**Tests:** 89/89 passed on first run, zero reruns  

Key principles proven: provenance-preserving decomposition, relationship preservation, explicit stop boundary, interpretation separation. All documented and verified.

## Git

- **Documentation commit:** `docs(confidence-engine): record focused deconstruction repeatability`
- **Working tree:** clean after this session's commit

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*This chapter records the initial-decomposition v0.61 experiment line. The line is frozen for the current MVP stage. See `docs/current-handoff.md` §CURRENT MVP DIRECTION.*