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Record W2898159221 · doi:10.1590/1980-5918.031.ao39

Motor development’s curves of premature infants on the first year of life according to Alberta Infant Motor Scale

2018· article· en· W2898159221 on OpenAlexaboutno aff
Raquel Saccani, Nádia Cristina Valentini, Keila Ruttnig Guidony Pereira, Cibelle Kayenne Martins Roberto Formiga, Maria Beatriz Martins Linhares

Bibliographic record

VenueFisioterapia em Movimento · 2018
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsPercentilePopulationMotor skillCategorizationMedicinePediatricsChild developmentScale (ratio)PsychologyDemographyPhysical therapyDevelopmental psychologyPhysical medicine and rehabilitationStatisticsEnvironmental healthGeographyMathematicsCartographyComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction: The motor trajectory of pre-term children is an important indicator of health during infancy, since alterations may be a signal for the need of professional intervention. Objective: To describe percentiles and motor development curves for Brazilian preterm infants in the first year of life, determining the reference values for categorization of motor performance assessed by the AIMS. Methods: Participated in this cross-sectional study 976 children born pre-term, newly-born to 12 months of corrected age. The Alberta Infant Motor Scale (AIMS) was used to assess participants’ motor development. The scores of the Brazilian norms were used as comparison criteria. Results: Children born pre-term showed lower scores compared to children born full-term indicating the need for a specific percentile curve for that population. The scores differentiated at P1 to P99 percentiles allowing for the categorization of children with typical development, at risk and with atypical development. At 0, 4, 8, 9, 10, 11 and 12 months an overlapping of extreme percentiles (P1, P5 and P10; P90, P95 and P99) was observed, but not in the other percentiles. Conclusion: The percentiles described indicate that preterm children presented lower motor performance than full-term children and AIMS has discriminant power for the clinical evaluation of these children. The developmental curves showed lower capacity for behavioral differentiation in the extreme percentiles.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.252
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 teacher head, 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

Citations7
Published2018
Admission routes1
Has abstractyes

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