Bibliographic record
Abstract
Prescribers and patients need a proper surveillance system for cognitive side effects A growing number of observational studies have shown the critical role of potentially inappropriate medications for increasing the risk of cognitive impairment. In a linked paper, Billioti de Gage and colleagues (doi:10.1136/bmj.g5205) extend the pharmacoepidemiological research on the adverse cognitive effects of benzodiazepines with an investigation of their link with Alzheimer’s disease.1 Their results suggest that long term exposure to benzodiazepines might be a modifiable risk factor for this condition. The authors conducted a nested case-control study of about 2000 older members of a public drug plan in the province of Quebec, Canada. They observed a cumulative dose-effect association between exposure to benzodiazepines (at least 90 days) and risk of developing Alzheimer’s disease and found that exposure lasting more than 180 days was associated with a nearly twofold increase in risk. In further analyses, they showed that longer acting benzodiazepines were associated with greater risk of developing Alzheimer’s disease compared with shorter acting benzodiazepines, adding support for a causal association. The interpretation of these findings is …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".