Implementación del sistema de gestión de seguridad y salud en el trabajo basado en la norma ISO 45001:2018 y su incidencia en la tasa de accidentabilidad en la empresa ESERMIN PERU.
Bibliographic record
Abstract
En este trabajo se propone implementar un SGSST según lo establecido en la Ley N.º 29783 para la empresa ESERMIN PERÚ S.A.C. El objetivo principal es cumplir con las normas vigentes, tanto nacionales como internacionales, y asegurar la salud y seguridad de los trabajadores, fomentando una cultura preventiva con la participación activa del personal. En la ejecución del estudio, se explica el procedimiento lógico y por fases que implica la puesta en funcionamiento de un SGSST, comenzando con su conceptualización del diagnostico y continuando con el análisis de factibilidad de su implementación en la compañía mencionada, lo que comprende un análisis de la misma, FODA y un análisis adicional con la herramienta PESTEL. En última instancia, su uso y los beneficios que tiene en la prevención de riesgos en el entorno laboral. Palabras Claves: Ley de SST, Implementación, SGS, Norma ISO 45001:2018, Prevención, Riesgos Laborales.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".