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Utilização de medicamentos pela população quilombola: inquérito no Sudoeste da Bahia

2013· article· pt· W1571854099 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista de Saúde Pública · 2013
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicPhytochemistry Medicinal Plant Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedical prescriptionFocus (optics)Action (physics)DrugEveryday life

Abstract

fetched live from OpenAlex

OBJECTIVE: To characterize the medication use by the quilombola population. METHODS: A population-based cross-sectional study was conducted with 797 adult quilombola in Vitória da Conquista, BA, Northeastern Brazil, in 2011. Analysis of variance was used to compare means of drugs by subject, according to demographic, socioeconomic and health-related behavior variables. Prevalence, prevalence ratios and their 95% confidence intervals were estimated. Multivariate analysis was carried out using Poisson regression with robust variance. RESULTS: The most widely consumed drugs by the population were those for the cardiovascular and nervous systems. Prevalence of medication use was 41.9%, significantly higher among women (50.3%) than men (31.9%). After adjusted analysis, medication use was associated with being female gender, being aged 60 or older, higher economic level, worse self-rated health, greater number of self-reported diseases and number of medical appointments. CONCLUSIONS: Strategies to improve rational drug use should preferentially focus on women and older adults. Thus, special attention should be given to promote rational prescription in everyday health services.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.029
GPT teacher head0.274
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it