Bibliographic record
Abstract
On behalf of the entire editorial team, we are very pleased to present you with the fourth issue of the University of Ottawa Journal of Medicine (UOJM). This edition marks the first of two installments in Volume 4. Since its re-launch in 2011, UOJM has continued its growth thanks to the collective efforts of the UOJM Leadership Team and our enthusiastic editors. The UOJM is a student-run, peer-reviewed journal that is dedicated to showcasing the wide variety of ideas and achievement of the Faculty of Medicine students. We accept many types of articles in both English and French, including scientific and non-scientific pieces. Our goals for this year were to increase both medical and graduate student involvement with the journal, and to promote our journal to different departments within the University of Ottawa and externally to other universities. Our ambitions were successfully accomplished this year with an editorial team size of 47 members and a record number of submissions
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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 | 0.013 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.088 | 0.089 |
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".