The Ptolemy project: a scalable model for delivering health information in Africa
Bibliographic record
Abstract
How is Africa to build up the medical research it needs? Doctors in African research communities are starved of access to the journals and texts their colleagues in more developed countries regard as fundamental to good practice and research. Isolation, burden of practice, and resource limitations make education and research difficult, but the rapid spread of access to the internet reduces these obstacles and provides an increasingly attractive means to disseminate information and build partnerships in education and research. \n \nThe role of electronic health information in building local capacity to find, publish, and implement solutions has been emphasised recently in Science,1 Nature,2 the Lancet,3,4 and the BMJ.5 The Global Forum for Health Research gives priority to interventions designed to build research capacity in developing countries and correct the disparity in health research.6 The Coalition for Global Health Research (Canada) has recently reported how a major effort now can make a substantial difference.7 Access to reliable health information has been described as “the single most cost-effective and achievable strategy for sustainable improvement in health care.”8 We are interested in helping to build research, teaching, and clinical capacity for neglected yet substantial problems such as injury, which kills 5.1 million people annually.9-11
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".