Patterns of international collaboration in cardiovascular research in sub-Saharan Africa
Bibliographic record
Abstract
The rising prevalence of cardiovascular disease in sub-Saharan Africa (SSA) constitutes a significant health and socio-economic challenge for the countries in the region. This study examines the patterns and scientific impact of international collaboration in cardiovascular research (CVR) in SSA. Bibliographic data from 2005 to 2014 were obtained from the Web of Science for cardiovascular-related publications with at least one author affiliated to an SSA country. The number of publications involving multiple SSA countries over this period accounted for less than 10% of the total number of multi-country publications that included at least one SSA country. Collaboration patterns reflected dominance by countries in Europe and North America, with South Africa accounting for the bulk of scientific collaboration in CVR within SSA. The findings indicate that pro-active strategies are needed to strengthen collaboration in CVR across SSA for the region to derive health and socio-economic benefits from locally conducted research.
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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 | 0.223 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.034 |
| Bibliometrics | 0.107 | 0.093 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.012 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".