Bibliographic record
Abstract
ical Writers Association will this year confer its prestigious President’s Award on Peggy Robinson, CMAJ’s for-mer manager of submissions and peer review, and former managing editor. Robinson was “honoured ” to receive the award, which was established in 1940 to improve the quality of medical communication. “AMWA provides a top-notch educational program for bio-medical communications through its high quality, hands-on workshops. ” In addition to serving as treasurer of the association’s Canada Chapter for 14 years, Robinson has been actively in-volved in organizing and presenting non-credit workshops and confer-ences. She continues to serve on the as-sociation’s budget and finance com-mittee, while working as a freelance manuscript editor at CMAJ. — Shawna Lessard, Ottawa Heading west: Alberta has supplanted BC as the El Dorado of the health care profession as it attracted more health care providers than any other province between 1996 and 2001, according to the Canadian Institute for Health Infor-mation. Alberta’s health workforce rose 4 % over that 5-year period as the province assumed the mantle as the na-tion’s preferred work destination, held for 10 years by British Columbia. —
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.206 | 0.167 |
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".