Criterios de salud en mujeres de diferentes edades Health criteria in women at different ages
Bibliographic record
Abstract
Se muestra el trabajo descriptivo realizado en el primer trimestre del año 2001 en el área de salud del Policlínico Docente "Dr. Mario Escalona Reguera", en Alamar, Ciudad de La Habana. En este, se reflejan entrevistas o encuestas a mujeres de diferentes edades, donde se precisan sus criterios acerca del concepto de salud, y en función de este identificar cómo evalúan su estado actual, qué piensan que deben hacer para mejorarla y qué realmente hacen en ese sentido. Los resultados principales obligan a pensar en la necesidad de crear grupos de reflexión sobre el tema para dar espacio a él desde sus diferentes aristas y lograr cambios de actitud a largo plazo entre ellas. Asombra el hecho de que las encuestadas adultas se asombren del tema sobre el que versaría la entrevista que se realizaría y reconozcan que nunca habían reparado en este asunto. The descriptive work carried out in the first quarter of 2001 in the health area of "Dr. Mario Escalona Reguera" Teaching Polyclinic, in Alamar, Havana City, is shown. The interviews and surveys done among women at different ages are presented. Their criteria about the health concept are determined and according to them it is possible to know how they evaluate their current health status, what they think they should do to improve it and what they really do in this sense. The main results make us believe that it is necessary to create groups to reflect on this topic, to approach it from different angles and to attain changes in their attitude in the long term. It is stressed the fact that the adult surveyed women were astonished when they heard about the topic of the interview and they themselves recognized that they had never considered it.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".