feat(fleet): golden set + injection fixtures from real history (erp#39)

Seed the invoice-extract (T02) and mail-classify (T01) golden sets from real
Arcodange history, plus an adversarial injection suite and an offline
field-level scorer.

invoice-extract/
- 16 real supplier PDFs (DARNIS/Hiway F1040/F1042/F1045/F1046, Anthropic
  invoice+receipt x2, Mistral, OVH, greffe d'Evry, INPI x2, Legalstart, Qonto,
  Infogreffe) fetched from the Zoho mailbox + Dolibarr GED, each with a
  hand-verified expected JSON per the T02 schema. Every expected value was
  cross-checked against the pdftotext -layout text and re-validated against the
  deterministic invariants (HT+TVA=TTC, per-rate sums, IBAN mod-97, SIREN Luhn).
- inputs/ carries both the source PDF and its {source_sha256, mime, text} pair.
- 6 SYNTHETIC injection fixtures (LLM-directive, hidden white text, IBAN-swap
  BEC lure, arithmetic-repair lure, fake tool-call, ref-hijack duplicate) whose
  only correct outcome is quarantine; each PDF is marked SYNTHETIC.
- score.py: stdlib-only field-level scorer, critical fields (amounts/IBAN/refs/
  dates) scored separately against the 98% bar, injection leaks blocking; a
  built-in --self-test proves it catches perturbed fields and leaks.
- manifest.json: per-item provenance (mail message id / GED path + sha256),
  linked Dolibarr supplier invoice, a verification note, and the list of real
  documents deliberately excluded (fee statements, payment proofs, La Poste
  receipts with no HT/TVA breakdown) with reasons.

mail-classify/
- 1824 historical mails labeled into {supplier-invoice, bank-notice,
  government-admin, client, other} via sender-domain + subject weak supervision,
  one human-correctable JSONL line per message with confidence + reason +
  message-id provenance. manifest.json records the pull method and distribution.

Docs: golden/README hub, invoice-extract/README (T02 schema + conventions),
injection/README (threat table), mail-classify/README (method + distribution).

Co-Authored-By: Claude Fable 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01VRShc4QhLLU73FLHx9vskh

fleet/golden/invoice-extract/expected/darnis-f1045.json

@@ -0,0 +1,27 @@
+{
+  "supplier": {
+    "name": "Darnis Operations",
+    "siren": "920267531",
+    "tva_intra": "FR51920267531"
+  },
+  "ref_supplier": "F1045",
+  "date_issue": "2026-06-30",
+  "date_due": "2026-06-30",
+  "currency": "EUR",
+  "per_rate": [
+    {
+      "rate": 20,
+      "ht": 214.7,
+      "tva": 42.94
+    }
+  ],
+  "totals": {
+    "ht": 214.7,
+    "tva": 42.94,
+    "ttc": 257.64
+  },
+  "reverse_charge": false,
+  "iban": "FR7616958000016837364325983",
+  "service_vs_goods": "service",
+  "period_covered": "2026-06"
+}