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--==========================================================================================
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-- 75. exam_response_areas.meta — rich recognition payload from the extraction service (P2)
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--==========================================================================================
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-- The extraction service (docling-exam-spike analyse contract) returns richer per-region detail than
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-- the thin first-pass could: per-option OMR box geometry + fill (boxes[]), select_n ("tick 2 of 5"),
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-- n_options, the expected unit/quantity for single-line answers, and the data_table an MC question reads.
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-- These have no dedicated columns; keep them in a jsonb sidecar so the canvas can render tick boxes /
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-- units / MC option counts without a column per attribute. Nullable, defaults to {}.
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alter table public.exam_response_areas add column if not exists meta jsonb not null default '{}'::jsonb;
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comment on column public.exam_response_areas.meta is
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'Extraction-service recognition detail: {n_lines, unit, quantity, n_boxes, n_options, select_n, box_form, boxes:[{x0,y0,x1,y1,fill}], table:{grid,n_cells}}. Rendered by the canvas; not authoritative for marking.';
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--==========================================================================================
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-- 76. exam_templates.extraction_meta — trust signal + provenance from the extraction service (P3)
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--==========================================================================================
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-- Records, per template, how the recognition was produced and whether it reconciled: the audit
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-- cover-total gate (cover_total vs detected_total, status, anomaly), the engine + slug used, and
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-- region counts. Lets the setup UI show "extraction: cover 100 = detected 100 ✓" (or flag an under-read),
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-- and lets the digital-text view resolve the paper's replica by slug. Nullable, defaults to {}.
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alter table public.exam_templates add column if not exists extraction_meta jsonb not null default '{}'::jsonb;
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comment on column public.exam_templates.extraction_meta is
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'Extraction-service provenance + trust gate: {engine, slug, audit:{cover_total,detected_total,status,anomaly}, counts}.';
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