Bibliographic record
Abstract
All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Can adian Medical Association. 1346 CMAJ, September 6, 2011, 183(12) © 2011 Canadian Medical Association or its licensors In this issue of CMAJ, Singh and colleagues1present a meta-analysis assessing the risk ofserious adverse cardiovascular events asso-ciated with the use of varenicline for smoking cessation. The paper raises additional questions about a drug that has already come under scrutiny by the US Food and Drug Administra-tion for neuropsychiatric safety concerns,2 and within the past month, the drug has been the focus of another warning regarding an association between it and serious adverse cardiovascular events.3 This new warning is based on observa-tions published in a randomized trial of vareni-cline for the treatment of tobacco dependence among participants with known cardiovascular
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.028 | 0.029 |
| Insufficient payload (model declined to judge) | 0.069 | 0.035 |
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".