Bibliographic record
Abstract
Surgery in Africa Monthly Reviews is a joint educational initiative of the Office of International Surgery, University of Toronto, and the College of Surgeons of East, Central and Southern Africa (COSECSA). Its objectives are to provide free, context-relevant curriculum material online to surgical trainees in low-income countries and to encourage surgeons in Africa and elsewhere to critically examine their practices. In general, the initiative encourages collaboration and exchange of experience among surgeons around the globe. Linked to the Ptolemy Project (www.ptolemy.ca/members), Surgery in Africa Monthly Reviews has published, since July 2005, reviews on surgical topics that are relevant to the very different conditions found in low-income African countries and that are based on a search of the current literature. It features a resource library on international surgery with links to other educational resources. Monthly topics are discussed on the online discussion group, http://groups.yahoo.com/group/Surgery-in-Africa/. Readers can access full-text articles from the bibliography by registering and creating an account through the Ptolemy Project website. New reviews are solicited from experts in the field with experience in the developing world. Participants in the initiative can earn credits under the Maintenance of Certification or Continuing Professional Development programs of the Royal College of Physicians and Surgeons of Canada. Reviewers from low-income countries receive an honorarium of Can$500 for their contributions.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.017 |
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".