Bibliographic record
Abstract
The below “Letter to the Editor” from Professor Rolf Håkanson pertains to the article by Montgomery et al. (2001a) and to the related correspondence in last year's October issue of Pharmacology & Toxicology (see references below). I do not feel that the new “Letter to the Editor” adds anything essential to the discussion. It has been presented to Montgomery and co-workers, who abstain from further comments. I completely agree with the joint editorial policy declaration published in several major journals by the Vancouver group (a.o. Lancet 2001 and previous reference Ugeskr. Laeger 2001) and I can assure our readers that PHARMACOLOGY & TOXICOLOGY continuously adheres to these principles. We hereby close for further publication on this topic.
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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 | 0.009 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.027 | 0.034 |
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".