Bibliographic record
Abstract
En 2006, la Society of Hospital Medicine describio el tratamiento del dolor como una competencia fundamental de los hospitalistas [1]. )Los hospitalistas deben poder describir los sintomas y signos del dolor, evaluar la intensidad del dolor utilizando herramientas de medicion validadas, formular un plan para el tratamiento del dolor, determinar la via, la posologia y las frecuencia adecuadas de los farmacos, determinar la dosificacion equianalgesica y ajustar los opioides hasta obtener el efecto deseado, prever y tratar los efectos adversos de los analgesicos, analizar con los pacientes los objetivos del tratamiento del dolor, utilizar un abordaje multidisciplinar para el tratamiento de los pacientes con dolor, utilizar recomendaciones de base cientifica, participar en la elaboracion de guias que faciliten el tratamiento eficaz del dolor, y participar en intentos de medir la calidad del control del dolor en el medio hospitalario* . El alivio del dolor es uno de los principios fundamentales para ser un medico. El objetivo de aliviar el dolor es la responsabilidad de todos los profesionales sanitarios y, como lideres de los equipos asistenciales hospitalarios, los hospitalistas deben estar en primera linea del tratamiento del dolor.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.977 | 0.975 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".