Considerations in designing an ideal medication-use system: Lessons from caring for the elderly
Bibliographic record
Abstract
Journal Article Considerations in designing an ideal medication-use system: Lessons from caring for the elderly Get access Jerry H. Gurwitz, M.D., Jerry H. Gurwitz, M.D. Executive Director Meyers Primary Care Institute, Fallon Healthcare System, and Professor of Medicine, University of Massachusetts Medical School, 100 Central Street, Worcester, MA 01608 Search for other works by this author on: Oxford Academic Google Scholar Paula Rochon, M.D, M.P.H., FRCPC Paula Rochon, M.D, M.P.H., FRCPC Scientist Kunin-Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care, Institute for Clinical Evaluative Sciences, and Assistant Professor, Departments of Medicine and Public Health Sciences, University of Toronto, Toronto, Ontario, Canada Search for other works by this author on: Oxford Academic Google Scholar American Journal of Health-System Pharmacy, Volume 57, Issue 6, 15 March 2000, Pages 548–551, https://doi.org/10.1093/ajhp/57.6.548 Published: 15 March 2000
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".