Bibliographic record
Abstract
En ma qualité de rédacteur en chef de la Revue Canadienne de Médecine Interne Générale (CJGIM) pendant un peu plus de six mois, j’ai eu le plaisir de faire connaissance et de travailler avec nos rédacteurs en chef adjoints, les Drs. Rodrigo Cavalcanti, Ameen Patel et John You, le comité de rédaction du journal et le personnel compétent de la Société Canadienne de Médecine Interne ( SCMI). J’ai également eu l’occasion de faire des réflexions sur les défis et les atouts de la Revue et souhaite vous faire part de notre point de vue sur ce projet et sur nos projets pour la CJGIM - votre Revue.
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 | 0.115 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.013 | 0.040 |
| Scholarly communication | 0.030 | 0.026 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.016 | 0.040 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".