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Record W2175301297

Surgery in Africa Monthly Reviews: introduction

2008· article· en· W2175301297 on OpenAlexaffabout
Pankaj Jani, Brian Ostrow

Bibliographic record

VenuePubMed Central · 2008
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineContext (archaeology)GlobeCertificationPtolemy's table of chordsDeveloping countryCurriculumMedical educationLibrary scienceEconomic growthOphthalmologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.246
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes2
Has abstractyes

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