Acreditación de servicios de prevención de riesgos laborales: hacia la mejora continua de la calidad
Bibliographic record
Abstract
espanolGetting the excellence and eficiency improvement of the prevention of laboral risks this paper propose the put in on of an Accreditation Agency. That Agency will be: independent, serious and with quality assurance thought the main agents participation on the way of laboral prevention risks. The Agency will have the responsability to design criteria and standards focusing the improvement ongoing quality as its done in the accreditation programms of healthcare facilities whith more experience and prestige in the world, as EEUU o Canada. espanolCon el objetivo de conseguir la excelencia y la mayor eficiencia en la Prevencion de Riesgos Laborales se propone la creacion de una Agencia de Acreditacion independiente, con credibilidad asegurada mediante la participacion de todos los agentes implicados en la Salud Laboral que sea la responsable de elaborar criterios y estandares de calidad orientados hacia la mejora continua a la manera como se realiza en los procesos de acreditacion de Organizaciones Sanitarias de mayor tradicion y prestigio en el mundo, como EEUU o Canada.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".