Inquérito de Saúde em Comunidades Quilombolas de Vitória da Conquista, Bahia, Brasil (Projeto COMQUISTA): aspectos metodológicos e análise descritiva
Bibliographic record
Abstract
The scope of this article was to present the methodology, preliminary descriptive results and the reliability of the instruments used in the COMQUISTA Project. It involved a cross-sectional study with adults (>18 years) and children (up to 5 years old) of Quilombola communities in Vitória da Conquista, Bahia. Data collection consisted of individual and household interviews, anthropometric and blood pressure measurements. A semi-structured questionnaire adapted from the Brazilian National Health Survey (PNS) was used and the interviews were conducted using handheld computers. 397 housing units were visited and 797 adults and 130 children were interviewed. The demographic profile of the Quilombolas was similar to the Brazilian population with respect to sex and age, however, they had precarious access to basic sanitation and a low socioeconomic status. The analysis of reliability revealed the adequacy of strategies adopted for quality assurance and control in the study. The methodology used was considered adequate to achieve the objectives and can be used in other populations. The results indicate the need for implementing strategies to improve the quality of life and reduce the degree of vulnerability of the Quilombolas.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".