Bibliographic record
Abstract
Fifteen of the 19 members of the editorial board of the CMAJ , the journal of the Canadian Medical Association (CMA), resigned last week over the firings of senior editors. Another editor has also resigned from the journal. That left the newly appointed acting editor in chief, Noni MacDonald, the editor emeritus, Bruce Squires, and three part time associate editors (of the original nine) trying to keep Canada's premier medical journal afloat. Scientific papers were said to be piling up at the rate of 25 to 30 a week. Dr MacDonald announced the resignations in a press release, saying that some previous members of the board had indicated their willingness to serve and that she will announce the creation of a new interim board soon. At the same time she explained in a letter posted on the journal's website (http://www.cmaj.ca/) “why we agreed to step into the breach,” and similarly the remaining three associate editors explained “why we are staying on.” In her letter Dr MacDonald wrote: “The crux of this interim period is the formation of a governance review …
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 | 0.019 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.079 | 0.072 |
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".