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Record W2589037707 · doi:10.33233/eb.v16i2.998

Aplicação do Modelo Calgary para Avaliação Familiar na Estratégia Saúde da Família

2017· article· pt· W2589037707 on OpenAlexaboutno aff
Ana Egliny Sabino Cavalcante, Antônia Regynara Moreira Rodrigues, Geilson Mendes de Paiva, José Jeová Mourão Netto, Natália Frota Goyanna

Bibliographic record

VenueEnfermagem Brasil · 2017
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesContext (archaeology)PhilosophyGeography

Abstract

fetched live from OpenAlex

Objetivou avaliar a dinâmica de uma famí­lia residente em um território de abrangência da Estratégia Saúde da Famí­lia. Trata-se de um estudo de caso, de abordagem qualitativa, realizado em Sobral/CE, tendo como referencial teórico o Modelo Calgary de Avaliação Familiar. Foi possí­vel compreender os sujeitos a partir do contexto e dinâmica familiar, e também observar o conví­vio e a interação entre os membros da famí­lia. As informações foram coletadas de setembro a dezembro de 2013 a partir de entrevista e análise de prontuários. A aplicação deste Modelo permitiu levantar os principais aspectos de sua estrutura, desenvolvimento e funcionamento, identificando os ví­nculos do usuário e seus relacionamentos no micro e macro espaço familiar, mostrando as redes de apoio social e as funções que desempenham no cotidiano. Assim, o Modelo Calgary emerge como recurso terapêutico importante, pois possibilita um tratamento voltado í vida do indiví­duo, considerando seu contexto, possibilitando ampliação das ações de cuidado.Palavras-chave: famí­lia, avaliação, Estratégia Saúde da Famí­lia.

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)0.010
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0030.003
Scholarly communication0.0100.007
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.171
GPT teacher head0.449
Teacher spread0.277 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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