在拉丁美洲的心血管的疾病研究: 比较 bibliometric 分析
Bibliographic record
Abstract
AIM:To investigate the number of publications in cardiovascular disease(CVD)in Latin America and the Caribbean over the last decade.METHODS:We performed a bibliometric analysis in PubMed from 2001 to 2010 for Latin America and the Caribbean,the United States,Canada,Europe,China,and India.RESULTS:Latin America published 4%of articles compared with 26%from the United States/Canada and 42%from Europe.In CVD,Latin America published 4% of articles vs 23%from the United States/Canada and 40%from Europe.The number of publications in CVD in Latin America increased from 41 in 2001 to 726 in 2010.CONCLUSION:Latin America,while publishing more articles than previously,lags behind developed countries.Further advances in research infrastructure are necessary to develop prevention strategies for this region.
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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 | 0.012 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.100 | 0.130 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".