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Record W4386987969 · doi:10.51161/conais2023/22949

PROGRAMA INTERSETORIAL DE APOIO AS COMUNIDADES RURAIS: RELATO DE EXPERIENCIA

2023· article· pt· W4386987969 on OpenAlexaff
Jéssica Pinheiro Carnaúba, Danielle Souza Silva Varela, Ellen Rose Sousa Santos, Francisca Laura Ferreira de Sousa Alves, Samy Loraynn Oliveira Moura, Marli Teresinha Gimeniz Galvão

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldEnvironmental Science
TopicRural Development and Agriculture
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsPolitical scienceHumanitiesMedicineArt

Abstract

fetched live from OpenAlex

INTRODUÇÃO: Evidenciamos a necessidade de ações intersetoriais em localidades mais afastadas das ofertas de serviço, surgindo a seguinte questão norteadora: como realizar atividades intersetoriais que alcancem os territórios mais afastados da sede do Município de Mombaça, Ceará? OBJETIVO: relatar o desenvolvimento de ações intersetorias nas localidades de difícil acesso da zona rural do município de Mombaça, Ceará. MÉTODOS: Estudo descritivo do tipo relato de experiência, a partir do desenvolvimento de uma intervenção intersetorial em locais da Zona Rural de Mombaça, Ceará, entre janeiro de 2022 a abril de 2023. RESULTADOS: Para a implementação dessas ações foi necessária complexa demanda de recursos materiais e humanos, sendo importante o estabelecimento de parcerias, além de organização e planejamento. Nesse sentido, no dia anterior a ação, todos os materias já ficavam preparados. A duração das atividades iniciavam em torno de nove da manhã, com encerramento as 17:00 horas. CONCLUSÃO: Iniciativas como essas se mostram importantes para a promoção da saúde de usuários que moram em locais de difícil acesso aos serviços, trazendo a importância da comunicação e integração entre diferentes setores. 

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.012

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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