Strengthening human genetics research in Africa: report of the 9th meeting of the African Society of Human Genetics in Dakar in May 2016
Bibliographic record
Abstract
The 9th meeting of the African Society of Human Genetics, in partnership with the Senegalese Cancer Research and Study Group and the Human Heredity and Health in Africa (H3Africa) Consortium, was held in Dakar, Senegal. The theme wasStrengthening Human Genetics Research in Africa.The 210 delegates came from 21 African countries and from France, Switzerland, UK, UAE, Canada and the USA. The goal was to highlight genetic and genomic science across the African continent with the ultimate goal of improving the health of Africans and those across the globe, and to promote the careers of young African scientists in the field. A session on the sustainability of genomic research in Africa brought to light innovative and practical approaches to supporting research in resource-limited settings and the importance of promoting genetics in academic, research funding, governmental and private sectors. This meeting led to the formation of the Senegalese Society for Human Genetics.
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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 | 0.043 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".