Prevalencia del hábito de fumar en adolescentes\nescolares en Asunción, Paraguay
Bibliographic record
Abstract
"Objetivos: Identificar la prevalencia de adolescentes fumadores en colegios públicos y privados en el departamento Central,Paraguay. Diseño: Transversal analítico. Lugar: Departamento Central, Paraguay. Participantes: Muestreo no probabilístico decasos consecutivos, dirigida a 478 adolescentes entre 12 y 17 años entre mayo y junio del 2006. Intervenciones: Cuestionarioestructurado y anónimo. Principales medidas de resultados: Chi cuadrado y Odds ratio de los factores de riesgo del hábitode fumar. Resultados: La prevalencia de tabaquismo fue de 11% de los cuales el 51% son varones. El 22% inicio el hábitode fumar a los 12 años. El 59% se inicio por curiosidad, el 11% fuma diariamente. Además el 27% acompaña el tabaco con elconsumo de alcohol. El 58% de los fumadores posee un entorno familiar fumador (OR= 1,76), el 67% de los fumadores tieneun entorno familiar inestable (OR=0,22), el 84% de los fumadores conoce las consecuencias de fumar (OR=3,27) y el 26% delos fumadores trabaja (OR=2,34). Conclusiones: Se encontró como factor de riesgo un entorno familiar fumador y trabajar,además el conocer las consecuencias del tabaquismo no se considera como factor protector."
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 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".