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Avaliação de famílias de bebês nascidos com muito baixo peso durante o cuidado domiciliar

2013· article· pt· W2023458134 on OpenAlexaboutno aff
Anelize Helena Sassá, Sônia Silva Marcon

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2013
Typearticle
Languagept
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologyPsychologyDemographyHumanitiesSociologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

Pesquisa convergente-assistencial cujo objetivo foi avaliar famílias de bebês nascidos com muito baixo peso baseando-se no Modelo Calgary de Avaliação Familiar. Participaram nove famílias que foram assistidas durante seis meses após a alta hospitalar do bebê. Os dados foram coletados por meio de visitas domiciliares e analisados com base nas categorias estrutural, de desenvolvimento e funcional propostas pelo Modelo. Subsistemas conflituosos estiveram presentes apenas em uma família e todas apresentaram em sua rede de apoio elementos oriundos de outros sistemas, que não o familiar. A colaboração dos pais, avós e filhos mais velhos nas tarefas domésticas permitiu às mães dedicarem mais tempo aos bebês e favoreceu a adaptação positiva e o equilíbrio familiar. Conviver com bebês nascidos com muito baixo peso exige que as famílias se organizem e se adaptem para o cuidado no domicílio, envolvendo mudanças nos papéis de cada membro familiar.

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)0.003
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.431
GPT teacher head0.516
Teacher spread0.085 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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