What does the Canadian Journal of Surgery mean to me, a community surgeon?
Bibliographic record
Abstract
The Canadian Journal of Surgery (CJS) now in its 50th year of publication has survived despite all the odds — and in my opinion rightly so. This indexed publication with contributions from general surgery, orthopedics and vascular surgery is one of the few remaining journals that appeal to the “generalist” surgeon. True, “cutting edge research” mostly gets published elsewhere, but the CJS with its potpourri of articles “tells it like it is” in Canada. Even though I may skim most articles, I come away with a sense of where the trends are going in related specialties. Authoritative editorials/opinion pieces by respected colleagues tackle some of the knotty issues of the day in surgical practice or the medicopolitical scene. The recently introduced and very popular Evidence-Based Reviews in Surgery assist one in honing critical appraisal skills and help to demystify statistics, while at the same time encouraging one to think about an important clinical topic. Surgical Biology for the Clinician encourages reflection on the underlying mechanisms of disease. The case notes often stump, delight and teach me — sometimes through the “but for the grace of God” principle! Resident research is strongly featured, and many of today's leaders got their feet wet for the first time publishing in the CJS. Those who have the privilege of reviewing articles for the journal before publication have the opportunity to influence content while interacting at arm's length with the authors. The CJS is celebrating an important milestone and deserves our continuing support both as readers and contributors.
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 | 0.016 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.016 | 0.020 |
| Scholarly communication | 0.035 | 0.009 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".