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Avaliação do desenvolvimento motor de bebês com deficiência auditiva

2023· article· pt· W4317881093 on OpenAlexaboutno aff
Amanda Brandão Domingues, Renata Escórcio, Beatriz de Castro Andrade Mendes

Bibliographic record

VenueRevista da Faculdade de Ciências Médicas de Sorocaba · 2023
Typearticle
Languagept
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedicineAudiologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Objetivo: Avaliar o desenvolvimento motor de bebês de zero a 18 meses com deficiência auditivade qualquer grau ou tipo com a utilização da EMIA. Método: Participaram da pesquisa, sete crianças, nascidas atermo com idade de 0 a 18 diagnosticadas com deficiência auditiva de qualquer tipo ou grau. O desempenho motor foi avaliado por meio da Escala Motora Infantil de Alberta (EMIA), composta por 58 itens, destes, 21 itens na postura prono, 9 itens em supino, 12 itens em sedestação e 16 itens em bipedestação. Resultados: Observou-se que três crianças apresentaram desempenho motor suspeito e uma apresentou desempenho motor de risco. Dentre estas crianças as posturas com maior dificuldade foram prono, sentado e em pé. Isto evidência que as posturas com maior dificuldade foram aquelas as quais é necessária maior integração sensorial, maior controle postural e equilíbrio. Conclusão: O presente estudo demonstrou que crianças com deficiência auditiva podem apresentar déficits no desempenho motor, principalmente com relação ao controle postural e equilíbrio. A EMIA mostrou-se um instrumento válido para a avaliação do desempenho motor dessa população.

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)0.003
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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.308
Teacher spread0.271 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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