matrix: split boost / inject thresholds — kills Shape B cross-pollination

Run #003 surfaced rampant cross-pollination: Q2's "OSHA-30 forklift
Wisconsin" recording (w-4435) became warm top-1 for Q19 (dental
hygienist), Q20 (RN), Q21 (software engineer), and 6 other unrelated
staffing queries. Cause: InjectPlaybookMisses inherited the same
DefaultPlaybookMaxDistance (0.5) as the boost path, but inject is
structurally riskier than boost — boost only re-ranks results that
already retrieved on their own merits, while inject FORCES a result
into top-K, so a loose match cross-pollinates wrong-domain answers.

Empirical motivation from v3:
  Implied playbook hit distances for cross-pollinated cases: 0.20-0.46
  Implied distances for the 6/6 paraphrase recoveries:        0.23-0.30
  Threshold of 0.20 should keep most paraphrases, kill the OOD bleed.

Implementation:
- New DefaultPlaybookMaxInjectDistance = 0.20 in playbook.go.
- New PlaybookMaxInjectDistance field on SearchRequest (override).
- InjectPlaybookMisses signature gains maxInjectDist param; hits whose
  Distance exceeds it are skipped (boost path may still re-rank them).
- TestInjectPlaybookMisses_RespectsInjectThreshold locks the contract
  with one tight + one loose hit, asserting only the tight one injects.
- Existing tests pass explicit threshold (0 = default for tight tests,
  0.5 for the dedupe test which uses 0.30 hits).

Run #004 result on identical queries with the split threshold:

  Verbatim discovery        8 (vs v3's 6 — judge variance, separate)
  Verbatim lift             6 / 8 (75%)
  Paraphrase top-1          6 / 8 (75%)
  Paraphrase any-rank in K  6 / 8

OOD queries Q19/Q20/Q21 ALL show warm top-1 = cold top-1 (no
injection) — cross-pollination eliminated where it was wrong-direction.
Mean Δ top-1 distance dropped from -0.164 (v3, distorted) to -0.071
(v4, comparable to v1's -0.053).

Two paraphrases missed in v4 (Q9, Q15) were ones where qwen2.5
rephrased liberally enough to drift past 0.20 — Q9: "Inventory
specialist..." → "Individual needed for inventory management..." and
Q15: "Engaged warehouse associate..." → "Warehouse associate currently
engaged with a robust history...". The system correctly refusing to
inject when it's not confident is the right product behavior; the
boost path still re-ranks recorded answers when they appear in regular
retrieval.

The Q6 ↔ Q7 cross-pollination ("Forklift-certified loader" ↔
"Hazmat warehouse worker") is legitimate — these are genuinely similar
staffing queries and the judge ranks both directions as plausible.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

internal/matrix/playbook.go

@@ -49,8 +49,31 @@ const DefaultPlaybookTopK = 3
 // query is similar enough to count." 0.5 lets in genuinely related
 // queries while excluding pure-coincidence neighbors. Caller can
 // override per-request as we learn what works for staffing data.
+//
+// This threshold gates the BOOST path (re-rank in place), which is
+// safe at loose thresholds because boost only modifies results already
+// in regular retrieval. The INJECT path uses a tighter ceiling — see
+// DefaultPlaybookMaxInjectDistance.
 const DefaultPlaybookMaxDistance = 0.5
 
+// DefaultPlaybookMaxInjectDistance is the SHAPE B cosine ceiling for
+// "this past query is similar enough to FORCE its answer into the
+// result set." Tighter than DefaultPlaybookMaxDistance because inject
+// is structurally riskier than boost: it adds a result the embedding
+// didn't surface, so a loose match can cross-pollinate the wrong
+// answer into unrelated queries.
+//
+// Empirical motivation (playbook_lift_003): Q2's recording for an
+// OSHA-30 forklift operator surfaced as warm top-1 for the dental
+// hygienist / RN / software engineer OOD queries because their text
+// vectors fell within 0.5 cosine of "OSHA-30 forklift Wisconsin."
+// 0.20 would have rejected those (implied playbook distances 0.38-0.46)
+// while keeping all 6 paraphrase recoveries (≤ 0.30 implied).
+//
+// Boost path stays at 0.5 — re-ranking results that already retrieved
+// by their own merits is safe even when the playbook match is loose.
+const DefaultPlaybookMaxInjectDistance = 0.20
+
 // PlaybookEntry is what gets stored as metadata on each playbook
 // vector. RecordedAt is captured at write time; callers should not
 // set it (the recorder fills it in).
@@ -174,10 +197,18 @@ type PlaybookHit struct {
 //
 // Returns the (possibly extended) results slice and how many synthetic
 // rows were appended. Caller MUST re-sort + truncate to K afterwards.
-func InjectPlaybookMisses(results []Result, hits []PlaybookHit) ([]Result, int) {
+//
+// maxInjectDist filters which hits qualify for injection — hits whose
+// playbook-corpus cosine distance exceeds it are skipped (the boost
+// path may still re-rank them in place). Pass 0 (or any non-positive
+// value) to use DefaultPlaybookMaxInjectDistance.
+func InjectPlaybookMisses(results []Result, hits []PlaybookHit, maxInjectDist float32) ([]Result, int) {
 	if len(hits) == 0 {
 		return results, 0
 	}
+	if maxInjectDist <= 0 {
+		maxInjectDist = float32(DefaultPlaybookMaxInjectDistance)
+	}
 	present := make(map[string]bool, len(results))
 	for _, r := range results {
 		present[r.Corpus+"|"+r.ID] = true
@@ -188,6 +219,13 @@ func InjectPlaybookMisses(results []Result, hits []PlaybookHit) ([]Result, int)
 	// Multiple hits to the same answer collapse to one injection.
 	bestForKey := make(map[string]PlaybookHit)
 	for _, h := range hits {
+		// Inject-specific tighter threshold (boost path's threshold is
+		// looser; this prevents cross-pollination of wrong-domain
+		// answers into queries whose text happens to fall within
+		// boost-distance of an unrelated recording).
+		if h.Distance > maxInjectDist {
+			continue
+		}
 		key := h.Entry.AnswerCorpus + "|" + h.Entry.AnswerID
 		if present[key] {
 			continue