docs: chunking/OCR re-index lever measured negligible — do not re-index

docs/chunking-ocr-reindex-lever-finding-2026-07-08.md

@@ -0,0 +1,91 @@
+# Chunking / OCR-repair re-index lever — measured finding (2026-07-08)
+
+**Verdict: negligible / neutral. Do NOT build config-gated chunking and do NOT re-index for
+this. Revisit only on a NEW, real golden miss that traces to a flattened dual-column table
+AND a config-gated chunking change that lifts `content_mrr@10` above baseline in eval.**
+
+This records a Phase-A offline measurement so the "last high-value retrieval lever"
+(table/heading-aware chunking + OCR repair, then a controlled re-index) is not re-litigated.
+It is the same call, on the same evidence standard, as the wrapped-dose-unit issue
+(measured 0.03%, correctly not re-indexed — see `npm run measure:wrapped-dose-units`).
+
+All figures below are from read-only queries against the live `Clinical KB Database`
+project (`sjrfecxgysukkwxsowpy`) on 2026-07-08. No worker, no re-index, no spend.
+
+## Why the re-index was gated
+
+- Enrichment coverage is already ~100%: **2065 docs / 69,334 chunks (all embedded) /
+  111,991 index units / 2065 `document_index_quality` rows**. Re-embedding the same text
+  buys nothing (see `docs/reindex-runbook.md`); a re-index only pays off if chunk
+  boundaries change (heading/table-aware) or the text changes (OCR repair).
+- Retrieval is already strong: `content_mrr@10 ≈ 0.90`, `document_recall@5 =
+content_recall@5 = 1.0` on the 24-case golden set — recall headroom is zero.
+- A full re-index re-embeds ~69k chunks against OpenAI = real spend, and needs explicit
+  owner go.
+
+## Finding 1 — `noisy_unit_rate` is a red herring (visual coverage, not corruption)
+
+`document_index_quality` was read as flagging ~495 docs for "dropped-letter OCR corruption"
+via `noisy_unit_rate > 0.2`. That is a misread of the column.
+
+- It is computed as `noisy_unit_rate = max(0, 1 - typed_unit_coverage)` where
+  `typed_unit_coverage = visual_units / total_units`
+  (`supabase/functions/indexing-v3-agent/index.ts`). It measures the fraction of a doc's
+  index units that are **not** visual-model units — a visual-coverage metric, unrelated to
+  text corruption.
+- On live it is **saturated at 1.0 for all 1,779 docs** that carry the signal, purely
+  because `visual_units = 0` corpus-wide (the visual-unit path was not populated on these
+  rows). The identity `noisy_unit_rate = 1 - visual_units/total_units` holds exactly
+  (0 violations).
+- Gotcha for future queries: `document_index_quality.metrics` is a JSON **array**, and the
+  `indexing_v3_agent` payload is a _stringified_ JSON element inside it. Extract with
+  `jsonb_array_elements_text(metrics)` filtered to elements `like '%indexing_v3_agent%'`,
+  then cast to `jsonb`.
+
+## Finding 2 — OCR corruption in index units is negligible (measured directly)
+
+Measured directly on all 111,991 rows of `document_index_units` (the layer the concern
+named; raw `document_chunks` answer context is clean):
+
+| Signal                                                              | Count  | % of 111,991 units |
+| ------------------------------------------------------------------- | ------ | ------------------ |
+| Exact cited signature (`p ycho`, ` ocial`)                          | **0**  | 0%                 |
+| Interior single-consonant proxy `[b-hj-z]`                          | 4,398  | 3.9%               |
+| — of which bullet-"o" glyph (`○`/`•` → "o", words intact; cosmetic) | 3,633  | 82.6% of proxy     |
+| — non-"o", excluding dose/dimension tokens (upper bound)            | **84** | **0.075%**         |
+
+The 84 residual units are almost all legitimate clinical/measurement tokens
+(`2 g IV`, `x 109/L`, `type b (Hib)`, `10cm x 15cm`). The only genuine artifacts are a
+couple of letter-spaced decorative banners (`A u s t r a l i a's S a f e s t...`) and a few
+truncated table cells — all in non-clinical text.
+
+The index-unit build path does not introduce corruption: `buildUnit` →
+`clinicalVocabularySearchText` only **appends** vocabulary terms and `compact` only
+truncates — neither drops or spaces out letters (`src/lib/document-index-units.ts`,
+`src/lib/clinical-vocabulary.ts`).
+
+## Finding 3 — table/heading-aware chunking is already implemented
+
+`src/lib/chunking.ts` already provides the mechanisms the lever proposed to add:
+
+- `detectHeading`, `extractSectionHeadings`, `headingLevel` (heading-aware).
+- `isTableBlock` / `chunkTableBlock` (table-aware; pipe-delimited blocks chunked
+  separately rather than flattened into prose).
+
+Live confirms it is working:
+
+- `section_path` is populated on **100%** of 69,334 chunks; `section_heading` on 42%.
+- Chunks are well-bounded — p50 996, p90 1,239, max 2,700 chars; only 435 chunks (0.6%)
+  exceed 2,400 chars. There is **no run-on flattening** at the chunk-size level.
+- 4,608 chunks (6.6%) already carry markdown table rows.
+- The dual-column "inpatient / community" concern matches only 219 chunks on the near
+  pattern, mostly ordinary prose. The genuinely scrambled cases are **flowcharts**
+  (boxes + arrows) that text chunking cannot linearize — those belong to the visual/image
+  extraction path, not `chunking.ts`.
+
+## Bottom line
+
+Neither lever clears the bar. OCR repair addresses ~0.075% of units (mostly non-clinical
+decoration); table/heading-aware chunking already exists and chunks are healthy; retrieval
+recall is already maxed. A re-index would spend real OpenAI budget on ~69k chunks for ~0
+expected retrieval gain. **Stop.**

docs/reindex-runbook.md

@@ -57,6 +57,7 @@ The preflight response also includes active job counts and job metadata for oper
 - Do not enable inline enrichment during recovery unless core indexing is stable.
 - Do not run imports, reindexing, queue recovery mutations, or evals when `npm run supabase:recovery-status` reports `supabase_unavailable`.
 - Do not use `--force-large-import` unless Supabase health is stable and you have intentionally chosen a larger import wave.
+- Do not re-index to fix "OCR corruption" or to add table/heading-aware chunking without new evidence. Both were measured negligible/neutral on 2026-07-08 (`noisy_unit_rate` is a saturated visual-coverage metric, not corruption; heading/table-aware chunking already exists and chunks are well-bounded). See `docs/chunking-ocr-reindex-lever-finding-2026-07-08.md`.
 
 ## Recommended recovery defaults