Bibliographic record
Abstract
Lira and Naimi Respond Marlene C. LiraMPH Timothy S. NaimiMD, MPH Affiliation Marlene C. Lira is with the Clinical Addiction Research and Education Unit, Department of Medicine, Boston Medical Center, Boston, MA. Timothy S. Naimi is with the Canadian Institute for Substance Use Research, University of Victoria, Victoria, BC, Canada. CopyRightCorrespondence should be sent to Marlene C. Lira, MPH, Clinical Addiction Research and Education Unit, Boston Medical Center, 801 Massachusetts Ave, 2nd Floor, Boston, MA 02118 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the "Reprints" link. CONTRIBUTORS M. C. Lira and T. S. Naimi worked together to draft and revise this letter. https://doi.org/10.2105/AJPH.2021.306707 Accepted: December 23, 2021 Published Online: March 23, 2022
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.025 | 0.012 |
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".