Proceedings of the Canadian Medication Appropriateness and Deprescribing Network’s 2023 National Meeting
Bibliographic record
Abstract
Polypharmacy, often defined as the use of five or more medications, is associated with a higher incidence of adverse drug events (ADEs) [ 1 , 2 , 3 ], and strongly linked to patient falls, cognitive impairment, hospitalizations, and death [ 1 ]. Despite these risks, polypharmacy represents a growing problem in many countries [ 4 , 5 , 6 , 7 ]. In Canada, approximately two thirds of adults over the age of 65 years take five or more prescription medications, and about a quarter (26.5%) take ten or more [ 8 ]. Factors including sex, income, and education are associated with polypharmacy, with higher rates observed in women, people of low income, and of lower education [ 9 ]. Polypharmacy is also costly, and represents an environmental burden, with medication production and disposal contributing to the healthcare sector’s carbon footprint [ 10 , 11 ].
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 | 0.001 | 0.002 |
| 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".