Retos a la Encuesta Nacional de Salud y Nutrición 2017
Bibliographic record
Abstract
Señor editor: La Encuesta Nacional de Salud 2017 deberá levantarse a cinco años de la Ensanut 2012, siguiendo la periodicidad esperada. La Ensanut 2017 será una herramienta fundamental para dar cuenta de tres importantes tendencias en el panorama de la salud de México: la predominancia de las enfermedades crónicas no transmisibles, el acercamiento a la protección financiera universal y la integración de redes de atención personalizadas. La Ensanut 2012 aportó información clave para las políticas en materia de: prevalencia del sobrepeso, obesidad, diabetes e hipertensión; así como en relación con las oportunidades para mejorar la calidad de la atención y el desencuentro entre actividad física y sedentarismo…
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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; both teacher heads 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".