Producción científica en Scopus de los institutos de salud especializados públicos de Perú, 2010-2022
Bibliographic record
Abstract
Objetivo: Evaluar la producción científica de los institutos de salud de Perú en Scopus, 2010-2022. Métodos: Estudio bibliométrico realizado en Scopus durante septiembre del 2022, en 14 institutos de salud especializados públicos de Perú. Incluimos estudios originales que tuvieran al menos un autor de alguno de los institutos. Resultados: Los institutos incluidos publicaron entre 0 y 347 artículos originales (H-index entre 0 y 51). Los institutos de la ciudad de Lima fueron los que tuvieron mayor producción. En los siete institutos con mayor producción, el porcentaje de artículos con autor corresponsal del instituto evaluado varió entre 22.3% y 36.7%, y el porcentaje de estudios que declararon ser financiados por el instituto varió entre 0% y 11.6%. Conclusión: La producción científica de los institutos evaluados fue heterogénea, a predominio de aquellos ubicados en Lima. Los institutos raramente participaron en el financiamiento de los estudios publicados.
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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 | 0.020 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.063 | 0.093 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".