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Record W4386296210 · doi:10.38087/2595.8801.209

A BIOESTATISTICA ASSOCIADA A EPIDEMIOLOGIA NA ATENÇÃO BÁSICA DE SAÚDE

2023· article· pt· W4386296210 on OpenAlexaff
Bruno Rocha de Souza, Luigì Santacroce, Henry Oh

Bibliographic record

VenueCOGNITIONIS Scientific Journal · 2023
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesSciELOPhilosophyMEDLINEPolitical science

Abstract

fetched live from OpenAlex

Objetiva-se por intermédio do presente estudo compreender como o conhecimento em bioestatística associado a epidemiologia influencia e pode ser aplicado na atenção básica de saúde.O estudo trata-se de uma revisão bibliográfica, possuindo carater exploratório e descritivo e desenvolvido pelo método qualitativo, através de artigos científicos e obras literárias que respondam os questionamentos levantados , sem recorte temporal, no idioma português, pesquisadas nas bases de dados LILACS, MEDLINE, BDTD, Google acadêmico, SciELO e periódicos da CAPES. Conclui-se que a bioestatística e a epidemiologia quando associadas, proprociona principalmente ao profissional de saúde na atenção básica, a entender e a compreender comportamentos ou situações que envolvam a população como um todo ou parte dela.

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 imitation

Not 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.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.110
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0160.022
Science and technology studies0.0020.003
Scholarly communication0.0080.006
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.109
GPT teacher head0.372
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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