Estudio aleatorio de tiempos de espera de pacientes según niveles de prioridad
Bibliographic record
Abstract
El objetivo del trabajo es determinar los tiempos de espera de pacientes según niveles de prioridad en el servicio de emergencia del Hospital Arzobispo Loayza, Lima - Perú. \nEs un estudio descriptivo, prospectivo, aleatorio en el que se calcula los tiempos de la primera asistencia médica, duración de la asistencia y la estancia total. Se utilizó el modelo andorrano y canadiense de triaje para determinar los niveles de prioridad. El percentil de Gómez fue útil para valorar resultados. \nLos tiempos promedio(minutos) de la primera asistencia médica fueron: prioridad I = 35.6 +- 55.8 , prioridad II = 50.8 +- 81.6, prioridad III = 31.5 +- 40.7, prioridad IV = 37.5 +- 67.8 y prioridad V = 40.8 +- 69.8. La duración y estancia total fueron directamente proporcionales a la gravedad. Según percentil de Gómez los niveles de prioridad I, II y III no cumplían con los tiempos establecidos. \nEl gran aumento de la demanda en los servicios de emergencia ocasiona tiempos de espera prolongados que afectan negativamente la atención de los pacientes más graves.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".