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Record W4220871535 · doi:10.36239/revisa.v11.n1.p69a80

O conhecimento a respeito da Manobra de Heimlich por mães da rede social Facebook

2022· article· pt· W4220871535 on OpenAlexaff
Gabriele Soares da Silva, Leila Batista Ribeiro, Lauren Canabarro Barrios Salles, Anna Júlia Veras de Lima, Cristiane Machado do Vale de Andrade, Vanessa Silva Lima, Alberto César da Silva Lopes

Bibliographic record

VenueRevista de Divulgação Científica Sena Aires · 2022
Typearticle
Languagept
FieldPsychology
TopicPsychology and Mental Health
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

Objetivo: analisar o conhecimento a respeito da Manobra de Heimlich por mães da rede social Facebook, tendo como problema de pesquisa o seguinte questionamento: “Durante o pré-natal na rede pública a mãe recebeu orientações sobre a manobra de Heimlich? Que conhecimento as mães tem sobre a manobra de Heimlich.” Método: Foi utilizada a abordagem qualitativa e método descritivo para este estudo, seguindo os pressupostos de Ludke e André (1986). Resultados: Foram entrevistadas 7 mulheres com idade entre 23 e 40 anos que responderam os questionamentos a respeito da Manobra de Heimlich no pré-natal e falaram sobre seus conhecimentos prévios a respeito do tema. Conclusão: As entrevistas realizadas revelam que as mulheres possuem conhecimento superficial a respeito da Manobra de Heimlich, no entanto esse conhecimento não foi obtido em seu pré-natal, mas sim por conta própria ou por necessidade. Descritores: Engasgo; Manobra De Heimlich; Pré-Natal.

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)0.005
metaresearch head score (Gemma)0.021
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 score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.060
GPT teacher head0.377
Teacher spread0.317 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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