# Rubric V9 — claim-level prose equivalence (contract 2.0.0 with addenda 4 and 5)

You compare claims of a published review (the target) with a generated review. You never see how the generated review was produced; you judge only the text.

**Target claims** are listed one per line with an id (from the abstract's results and conclusions and, when present, the plain language key messages). For each target claim decide a label. Direction categories are: **benefit**, **harm**, **little or no difference**, **uncertain**.

| label | meaning |
|---|---|
| `matched` | the generated review states the same finding: same comparison and outcome, same direction category, and the same certainty level (high "results in", moderate "probably", low "may", very low "very uncertain"); a numeric estimate, if the target gives one, agrees to the stated precision |
| `partial` | same comparison and outcome, and either the same direction with the certainty one level apart, an estimate beyond rounding or a missing qualifier (population, time point), or a **neighbouring** direction category (benefit or harm against "little or no difference"; any direction against "uncertain") |
| `missing` | the generated review makes no statement about this comparison and outcome |
| `contradicted` | the generated review states the **opposite** direction (benefit against harm), or a certainty two or more levels apart, or a conclusion the target explicitly rejects in words (a neighbouring category alone is not such a rejection) |

**Two conventions for one imprecise finding (addendum 5, A11).** When the 95% confidence interval includes or reaches no effect (1 for ratios, 0 for differences), as shown in the target claim or the generated sentence, reviews word the same finding in two ways: a hedged direction from the point estimate ("may be slightly higher", "likely results in a slight reduction") or "little or no difference". Treat these as the **same direction category** when the estimate agrees to the stated precision and the certainty level is the same; label by the other conditions, set `convention_equivalent` to `true`, and name the interval in `note`. "Uncertain" against a stated direction stays a neighbouring category: very-low-certainty wording carries no direction. Otherwise set `convention_equivalent` to `false`.

A claim with several findings takes the label of its worst part. Note the parts in `note`.

**Information the generated review could not have** (stage-isolated runs; listed below the claims as "SI input"). If a claim, or part of one, needs information that is not in that input, set `input_limited` to `part` or `all`. Quote that part verbatim from the target claim in `input_limited_text`, and choose one `input_limited_category`:
- `study_status_or_search`: counts or lists of excluded, ongoing or awaiting studies, or search and screening facts not in the protocol input;
- `review_process`: update schedules or plans not in the protocol input;
- `certainty_reasons`: why certainty was rated as it was (levels themselves are in the input);
- `results_outside_analyses`: findings that are in no analysis listed in the input.

For `part`, label only the remainder. For `all`, still give your best label. Otherwise set `input_limited` to `none`.

**Target deviations.** The target's own Summary of findings ratings are listed below the claims. If a target claim's wording implies a certainty level for a comparison and outcome that differs from the target's own rating there, set `target_deviation` to the implied level and `td_row` to the listed row's id. An unhedged "are effective" or "reduces" implies high; "likely" or "probably" implies moderate; "may" implies low; "very uncertain" implies very low. Otherwise set `target_deviation` to `null`.

Rules: judge meaning, not wording. A target claim about "no studies found" for an outcome is matched by a generated statement that no studies reported it. Quote the generated sentence you used (up to 40 words) for every label except `missing`. Output JSON only:
`{"claims": [{"id": "T1", "label": "matched|partial|missing|contradicted", "generated_quote": "...", "note": "...", "input_limited": "none|part|all", "input_limited_text": "", "input_limited_category": "", "target_deviation": null, "td_row": null, "convention_equivalent": false}]}`