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Record W4318762636 · doi:10.55232/1086001.11

ASSISTÊNCIA DE ENFERMAGEM FRENTE AO ABANDONO DO ALEITAMENTO MATERNO EXCLUSIVO (AME)

2023· book-chapter· pt· W4318762636 on OpenAlexaff
Lucas Santos Sampaio, Gilva Izidorio Carvalho, Eliabe Silva Reis, Maiange Pereira Santos, Andressa Karolayne Melo Frota, Geísa de Morais Santana

Bibliographic record

VenueInstituto Scientia eBooks · 2023
Typebook-chapter
Languagept
FieldSocial Sciences
TopicAcademic Research in Diverse Fields
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

RESUMO: Introdução: Dito isto, percebe-se que os enfermeiros desempenham um papel admirável como base para essa prática, e, oportunidades educativas devem ser identificadas e fornecidas para a correta orientação das gestantes e puérperas acerca da importância do aleitamento materno exclusivo (AME) e do manejo da lactação.Objetivo: O objetivo desta revisão foi avaliar a atuação do enfermeiro diante o abandono do aleitamento materno exclusivo (AME) em crianças com faixa etária até seis meses de idade.Método: Trata-se de uma revisão de literatura do tipo integrativa.Resultados e Discussões: Os resultados achados permitem o fortalecimento do problema, ou seja, algumas mães se localizam em situação de muita vulnerabilidade para realizar o ato de amamentar, assim, permitindo um abalroamento mais efetivo através da preparação de estratégias características diante suas precisões.Conclusão: Portanto, as ações para a efetiva implementação do AME não estar sujeito apenas aos profissionais de saúde ou aos enfermeiros, mas necessitam envolver diversos outros atores, dentre eles, o estado, a sociedade, e a 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.139
GPT teacher head0.377
Teacher spread0.238 · 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 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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