fix(backend): read a tooth code whatever script its digits are in
The extraction model transcribes Persian speech, so it can hand back "۲۶" in Persian digits or "2 6" from a digit-by-digit dictation. Both were compared literally against /^[1-8][1-8]$/, missed, and fell through to the positional branch with no quadrant — where the tooth was reported as "not understood". The clinician loses a tooth and is told the words were the problem. normalizeFdiCode() now runs at both the branch choice and the final validation, so the two cannot disagree. toLatinDigits moves out of jalali.ts into common/digits.ts: it was exported but unused in production, and a tooth module reaching into the calendar module would read as an accident. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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@@ -1,3 +1,4 @@
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import { normalizeFdiCode } from '../../common/fdi';
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import type {
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ConnectedSpanIntent,
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DueIntent,
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@@ -180,7 +181,10 @@ const FDI_SHAPE = /^[1-8][1-8]$/;
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function toToothIntent(wire: WireToothIntent | undefined | null): ToothIntent {
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const spoken = typeof wire?.spoken === 'string' ? wire.spoken : '';
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const fdi = typeof wire?.fdi === 'string' ? wire.fdi.trim() : '';
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// Persian digits and digit-by-digit dictation ("۲۶", "2 6") are FDI codes that do not
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// match literally; without normalising first they fall through to the positional branch
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// with no quadrant and are reported as unresolved.
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const fdi = normalizeFdiCode(wire?.fdi);
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// Only take the explicit branch for something actually FDI-shaped. A model that emits
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// fdi:"6" alongside correct arch/side/position would otherwise lose the tooth entirely.
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if (FDI_SHAPE.test(fdi)) {
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