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Record W1581404802 · doi:10.5020/2003

Determinação de fatores de risco para a queda infantil a partir do modelo Calgary de avaliação familiar

2012· article· pt· W1581404802 on OpenAlexaboutno aff
Aline de Souza Pereira, Samira Valentim Gama Lira, Deborah Pedrosa Moreira, Isabella Lima Barbosa, Luiza Jane Eyre de Souza Vieira

Bibliographic record

VenueRevista Brasileira em Promoção da saúde · 2012
Typearticle
Languagept
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Objetivo: Determinar fatores de risco para quedas em crianças a partir do Modelo Calgary de Avaliação Familiar (MCAF). Método: Estudo com abordagem qualitativa, no qual foram entrevistados 6 familiares de crianças que se encontravam internadas em um hospital de emergência em Fortaleza-Ceará devido a queda, no período de agosto a setembro de 2005. Conforme o MCAF realizou-se o genograma e ecomapa de duas famílias. Resultados: Através do genograma e ecopama observou-se que a família (1) é monoparental, com seis filhos, católica, recebe um salário mínimo, frequenta a escola e Unidade Básica de Saúde da Família (UBSF). A família (2) é nuclear, com dois filhos, católica, recebe tres ou mais salários mínimos, frequenta a escola, trabalho e UBSF. Conclusão: O Modelo Calgary de Avaliação Familiar proporcionou conhecer as estruturas familiares de crianças que sofreram quedas e auxiliou na definição dos fatores de risco que existem no seio familiar e nos ambientes sociais que essas crianças frequentam. A renda familiar, o número de filhos, a presença ou ausência paterna, a escolaridade e falta de espaços que dão suporte à educação representam fatores de risco para esses acidentes.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.055
GPT teacher head0.360
Teacher spread0.305 · 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 teacher head, not a consensus.

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
Published2012
Admission routes1
Has abstractyes

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