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Record W4321497521 · doi:10.3390/ijerph20053819

Motor Development Comparison between Preterm and Full-Term Infants Using Alberta Infant Motor Scale

2023· article· en· W4321497521 on OpenAlexaboutno aff
Jooyeon Ko, Hyun Kyoon Lim

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2023
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsFull TermTerm (time)Motor activityScale (ratio)Motor skillMedicinePediatricsPsychologyPhysical medicine and rehabilitationDevelopmental psychologyGeographyBiologyPhysicsPregnancy

Abstract

fetched live from OpenAlex

The Alberta Infant Motor Scale (AIMS) was developed to evaluate the motor development of infants up to 18 months of age. We studied 252 infants in three groups (105 healthy preterm infants (HPI), 50 preterm infants with brain injury (PIBI), and 97 healthy full-term infants (HFI) under 18 months, corrected age (CoA)) using AIMS. No significant differences were found among HPI, PIBI, and HFI in infants less than 3 months old, yet significant differences were noted in positional scores (p < 0.05) and total scores for those four to six months of age and seven to nine months of age. A significant difference was also found in standing items for infants over 10 months (p < 0.05). After four months, there was a difference in motor development between preterm (with and without brain injury) and full-term infants. In particular, there was a significant difference in motor development between HPI and HFI and between PIBI and HFI at four to nine months, when motor skills developed explosively (p < 0.05). After four months, motor developmental delays (10th ≥) were observed in HPI and PIBI at rates of 26% and 45.8%, respectively. Midline supine development, a representative indicator of early motor development, was slower even in healthy preterm infants than in full-term infants. AIMS has a good resolution to discriminate preterm infants who are showing insufficient motor development from 4 months to 9 months.

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)0.000
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 score0.064
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.099
GPT teacher head0.400
Teacher spread0.301 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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