Bibliographic record
Abstract
El estres ocupacional es un problema reconocido desde hace anos en los trabajadores sanitarios, y constituye un riesgo importante y especifico en los profesionales medicos. Influye en la satisfaccion por el trabajo que se realiza, en el bienestar psicologico y en la salud fisica, pero tambien puede afectar indirectamente a los pacientes a los que se intenta mejorar su salud. Recientes investigaciones muestran que, mientras un 17,8% de los empleados de actividades generales presenta signos de morbilidad psiquiatrica de origen laboral, en los de la sanidad llega a alcanzar entre el 22% y el 46%. El fenomeno se produce, especialmente, en los paises mas desarrollados (existen referencias de Estados Unidos, Canada, Australia, Nueva Zelanda, Reino Unido y Espana) pero tambien ocurre en estados con economias en transicion (Turquia, Pakistan), aunque se han publicado todavia pocas experiencias. Entre los trabajadores de la salud, se manifiesta fundamentalmente en intensivistas y anestesiologos-reanimadores, urgenciologos y emergenciologos prehospitalarios, aunque aparece tambien con menor intensidad en responsables de otras especialidades, incluso en generalistas y en personal de enfermeria.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".