Letter to the editor: <i>risk factors for cervical artery dissection</i> – <i>a systematic review with meta-analysis</i>
Bibliographic record
Abstract
We commend Jacobs et al for their article, ‘Risk factors for cervical artery dissection: a systematic review with meta-analysis’, which addresses this important topic through a comprehensive review. The authors report adherence to guidelines outlined by the Joanna Briggs Institute (JBI) for aetiology, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement, and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) for observational studies. While the review transparently describes methodological challenges and cautions readers about the low certainty of evidence, in our view, it does not fully adhere to the methodological and reporting standards outlined by these guidelines. Moreover, we highlight key methodological limitations of the review.
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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 | 0.023 | 0.154 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.020 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".