# Evaluate new predictions and replay the paper Install `requirements.txt` in a Python 3.12+ environment. The verified runtime and exact package versions are in `protocol/verified-runtime.json`. All commands below run on CPU, use local files, and make no model/API calls. Run from this dataset folder, with outputs outside it so the frozen manifest stays valid. ## New model predictions Use only `image` and `question` as model inputs. Read the exact prompt and schema from `protocol/prompt.json`. Obtain GQA inputs using `RECONSTRUCTION.md` first. Write one JSON object per input in `predictions.jsonl`: ```json {"item_id":"item-0001","answerable":false,"answer":null,"reason":"The needed value is not visible."} ``` That is a format example, not a prescribed answer for other inputs. Retain each stable item ID. For a terminal malformed model output use: ```json {"item_id":"item-0001","status":"invalid_schema","terminal_invalid":true,"parsed":null} ``` One row is required for every selected input. Do not submit both examples for the same ID. Missing/duplicate/unexpected IDs or incomplete state groups cause the scorer to fail rather than silently shrink the denominator. Invalid final outputs count as failures. A valid answerable decision with a null answer can pass decision scoring but fails answer correctness. Unanswerable decisions must have a null answer and all valid outputs need a nonempty reason. ```bash python scripts/score_hf_dataset.py --predictions ../predictions.jsonl \ --sources plotqa clevr gqa --output ../scores.json ``` For a single subset, supply only its predictions and e.g. `--sources plotqa`. Output includes exact counts, per-state failures, per-view decision accuracy, all-decisions-correct groups, supported-answer accuracy, class-balanced failure, and complete joint answer/abstention success. Chart answers use the paper's conservative exact-rational parser (no numeric tolerance). Scene scoring first checks exact rationals, then Unicode NFKC, case and whitespace normalization; it does not infer synonyms. A percentage marker follows the historical parser and is not automatically divided by 100. The GQA flag in the metadata defines the same 376-group location sensitivity stratum as the paper. The supplied saved-response replay reports both strata. ## Reproduce reported statistics ```bash python scripts/replay_hf_statistics.py --output ../replay ``` This checks all 72,000 scoring projections, recomputes all 18 model/domain cells and the paper's 10,000-draw paired group bootstrap intervals, compares the full analysis JSON to the frozen expected result, regenerates tables and chart diagnostics, verifies the 5,000 chart view-to-proof identity joins, and runs the new-prediction scorer against all six saved configurations. It also checks the finite-study counts and enumeration/SMT agreement from saved per-case records. It does not regenerate the finite solver-study witnesses, raw generations or historical serving traces. GQA question-ID tokens replace upstream question text consistently in numerical replay; reconstruction checks the actual text. The supplementary shortcut and answer-error counts can also be checked directly: ```bash python scripts/verify_argument_evidence.py --inputs inputs \ --finite-results evidence/finite/original-results.jsonl.gz \ --solver-results evidence/finite/solver-results.jsonl.gz \ --output ../supplementary-counts.json ``` ```bash python scripts/verify_hf_dataset.py --workers 8 --output ../verification.json ``` This verifies the frozen file manifest, loads all three configurations through Hugging Face Datasets, decodes and hashes all 9,000 bundled images, checks every state group and unique source-image identity, verifies all 1,000 complete chart proofs against their evaluated PNGs, and replays chart/CLEVR source programs. The GQA source-program and image check is run by the separate reconstruction command. A small machine may reduce `--workers`. To run only the chart proof checker: ```bash python scripts/verify_bounded_witness_bundle.py \ --proofs evidence/plotqa/bounded-witness-proofs.jsonl.gz \ --workers 8 --output ../chart-proof-verification.json ``` The prepared package includes historical counts plus current validation reports. Reports are evidence of the checks they describe, not a guarantee about every upstream annotation or a substitute for independent scientific review.