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Record W2903334352 · doi:10.5216/ree.v20.48578

Amamentação e tecnologias mHealth: análise dos aplicativos móveis para tablets e smartphones

2018· article· pt· W2903334352 on OpenAlexaff
Carolina Maria de Sá Guimarães, Maria Esther Imamura, Solina Richter, Juliana Cristina dos Santos Monteiro

Bibliographic record

VenueRevista Eletrônica de Enfermagem · 2018
Typearticle
Languagept
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Os objetivos deste estudo foram:identificar os aplicativos móveis sobre amamentação em português e analisar o conteúdo destes aplicativos, com base nas recomendações oficiais. Trata-se de estudo transversal e descritivo, que investigou os aplicativos nas lojas virtuais Play Store e Apple Store.Foram analisados 12 aplicativos. Todos apresentavam a função de cronômetro, o que está em desacordo com a recomendação de livre demanda. As figuras mais utilizadas pelos aplicativos foram desenhos animados com uso de chupetas e mamadeiras (66,7%/n=8), animais mamíferos relacionando-os à alimentação humana (16,7%/n=2) e fotos produzidas em estúdio (8,3%/n=1). Apesar de os aplicativos apoiarem a amamentação, algumas das informações disponibilizadas são contrárias às recomendações oficiais e não representam a realidade da mulher que amamenta.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.005

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 head0.085
GPT teacher head0.383
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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