Cochrane Cameroon: bringing cochrane to francophone sub-Saharan Africa
Bibliographic record
Abstract
June 30th 2021 marks the launching of Cochrane Cameroon in Yaoundé, Cameroon. Cochrane Cameroon is the fourth geographical group of Cochrane in sub-Saharan Africa, following Cochrane South Africa (1997), Cochrane Nigeria (2006) and Cochrane Kenya (2021). All are part of the Cochrane Africa Network, formally established in 2017. Cochrane Cameroon is based in the Centre for Development of Best Practices in Health, at the Yaoundé Central Hospital in Cameroon, and is the base of the Francophone hub of Cochrane Africa [1]. The Francophone hub includes Benin, Burkino Faso, Cameroon, Congo, Democratic Republic of Congo, Ivory Coast, Madagascar, Mali and Senegal.
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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 | 0.028 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.158 | 0.042 |
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".