Lusk et al. Respond
Bibliographic record
Abstract
AffiliationsAnne C. Lusk is with the Department of Nutrition, Harvard School of Public Health, Boston, MA. Patrick Morency is with the Direction de santé publique de Montréal and the Département de médecine sociale et préventive, Université de Montréal, Montreal, Québec. Luis F. Miranda-Moreno is with the Department of Civil Engineering and Applied Mechanics, McGill University, Montreal. Walter C. Willett is with the Departments of Nutrition and Epidemiology, Harvard School of Public Health, and Brigham and Women’s Hospital, Harvard Medical School, Boston. Jack T. Dennerlein is with Bouvé College of Health Sciences, Northeastern University and the Department of Environmental Health, Harvard School of Public Health.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.022 | 0.015 |
| Insufficient payload (model declined to judge) | 0.054 | 0.029 |
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".