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Record W4213185378 · doi:10.3390/children9020270

Alberta Infant Motor Scale (AIMS) Performance of Early-Term Greek Infants: The Impact of Shorter Gestation on Gross Motor Development among “Term-Born” Infants

2022· article· en· W4213185378 on OpenAlexaboutno aff
Dimitrios Syrengelas, Eirini Nikaina, Paraskevi Kleisiouni, Tania Siahanidou

Bibliographic record

VenueChildren · 2022
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsGross motor skillGestationGestational ageFull TermMedicineTerm (time)PediatricsBayesian multivariate linear regressionMotor skillRegression analysisPregnancyBiology

Abstract

fetched live from OpenAlex

Early-term birth (37+0 to 38+6 gestational weeks) may have a negative impact on infants’ neurodevelopment compared to delivery at 39 weeks or beyond. The purpose of this study was to evaluate the gross motor development of early-term infants using the Alberta Infant Motor Scale (AIMS). A total of 1087 healthy infants (559 early-term and 528 full-term infants born at 39+0 to 41+6 weeks of gestation) were studied. Mean AIMS scores were compared between the two groups at monthly intervals. The impact of gestational age on total AIMS scores was assessed by linear regression, after adjustment for chronological age, sex and SGA. Mean total AIMS scores, albeit within normal range, were significantly lower in early-term than full-term infants at the 2nd, 6th, 7th, 8th and 12th month of age; differences between groups were within three points. In multivariate regression analysis, a longer gestation by one week had a positive impact on total AIMS score during the first year of life (β = 0.90; 95% CI 0.45, 1.35). In conclusion, early-term infants exhibit worse gross motor performance during the first year of life in comparison with their full-term peers; however, the differences between the two groups are small.

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 score0.013
Threshold uncertainty score0.969

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)0.0000.000

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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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