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agent/t_5c
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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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--==========================================================================================
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-- 78. exam_questions.command_word + preamble — richer recognition carried by the analyse contract v2 (WS-2)
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--==========================================================================================
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-- The extraction service (docling-exam-spike analyse.py v2, scripts/ANALYSE-CONTRACT.md) now carries two
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-- fields the thin v1 bridge dropped:
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-- * command_word — the primary command verb per part (calculate / explain / suggest / describe …), from
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-- structure.command_words / part_info.primary. Drives the question-tree command pill + future filtering.
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-- * preamble — the stem prose that introduces a question/part (structure.preamble_by_label), as a
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-- jsonb sidecar {n, text:[…lines], nontext:[{kind,cls,page}], bands:[{page,y0,y1}]}. Kept as jsonb (not
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-- a column per line) so the tree/doc view can show the stem and the canvas can locate its band. The
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-- preamble band is ALSO emitted as a drawable context region (context_type='preamble'); this column is
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-- the authoritative text for the outline view.
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-- Both nullable; containers/parts without a detected command/preamble stay null. Additive + idempotent.
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alter table public.exam_questions add column if not exists command_word text;
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alter table public.exam_questions add column if not exists preamble jsonb;
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comment on column public.exam_questions.command_word is
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'Primary command verb for a leaf part (calculate/explain/suggest/describe/…), from the analyse contract v2 (structure command_words / part_info). Null for container questions or when none detected.';
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comment on column public.exam_questions.preamble is
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'Stem prose introducing this question/part, from the analyse contract v2 (structure.preamble_by_label): {n, text:[lines], nontext:[{kind,cls,page}], bands:[{page,y0,y1}]}. Authoritative text for the outline view; the band is also drawn as a context_type=preamble region.';
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