Bibliographic record
Abstract
These compliance proceedings under Article 21.5 of the DSU concerned measures adopted by the United States to comply with the Dispute Settlement Body (DSB) recommendations and rulings in US – COOL. In US – COOL, the DSB found that a certain US country-of-origin labelling (COOL) measure regarding muscle cuts of meat (the Original COOL Measure), and the administration of that measure, were inconsistent with certain aspects of the TBT Agreement and the GATT 1994. The United States' measure taken to comply with the recommendations and rulings of the DSB consisted of an amendment to the Original COOL Measure (the 2013 Final Rule). In these compliance proceedings, the Panel and Appellate Body referred to the 2013 Final Rule, together with the Original COOL Measure, as the Amended COOL Measure. The Amended COOL Measure was the focus of these compliance proceedings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.024 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".