Verapamil intoxication after substitution of immediate-release for extended-release verapamil
Bibliographic record
Abstract
Journal Article Verapamil intoxication after substitution of immediate-release for extended-release verapamil Get access Patrice Laberge, M.Sc., Patrice Laberge, M.Sc. Clinical Pharmacist Department of Pharmacy, Hôpital du Sacré- Coeur de Montréal (HSCM), Quebec, Canada Search for other works by this author on: Oxford Academic Google Scholar Pierre Martineau, M.Sc., Pharm.D., BCPS, Pierre Martineau, M.Sc., Pharm.D., BCPS Clinical Scientist, Clincial Pharmacist and Associate Clinical Professor Medical Division, Pfizer Canada, Kirkland, Quebec; HSCM,, Faculty of Pharmacy, University of Montreal (UM), Quebec Address correspondence to Dr. Martineau at Pfizer Canada, 17,300 Trans-Canada Highway, Kirkland, Quebec, Canada H9J-2M5. Search for other works by this author on: Oxford Academic Google Scholar Herawaty Sebajang, M.D., Herawaty Sebajang, M.D. General Surgery Resident Faculty of Medicine, University of Montreal (UM), Montreal, Quebec Search for other works by this author on: Oxford Academic Google Scholar Guy Lalonde, M.D., FRCP Guy Lalonde, M.D., FRCP Associate Clinical Professor and Cardiologist Department of Medicine, HSCM, and Faculty of Medicine, UM Search for other works by this author on: Oxford Academic Google Scholar American Journal of Health-System Pharmacy, Volume 58, Issue 5, 1 March 2001, Pages 402–405, https://doi.org/10.1093/ajhp/58.5.402 Published: 01 March 2001
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".