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Record W2031093317 · doi:10.1097/pep.0b013e3181e94481

Clinimetric Properties of the Alberta Infant Motor Scale in Infants Born Preterm

2010· article· en· W2031093317 on OpenAlexaboutno aff
Tamis W. Pin, Katy de Valle, Bev Eldridge, Mary P. Galea

Bibliographic record

VenuePediatric Physical Therapy · 2010
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsIntraclass correlationIntra-rater reliabilityInter-rater reliabilityPediatricsReliability (semiconductor)MedicineMovement assessmentMotor skillGestationGross motor skillPhysical therapyPsychologyDevelopmental psychologyRating scalePsychometricsPregnancy

Abstract

fetched live from OpenAlex

In Brief Purpose: The Alberta Infant Motor Scale (AIMS) is a standardized motor assessment for young infants. This study aimed to examine the reliability of the AIMS in a group of infants born at or before 29 weeks of gestation. Methods: Fifty-nine infants born preterm were recruited. Two experienced pediatric physical therapists participated in this reliability study. Infants were assessed at 4, 8, 12, and 18 months corrected age (CA). Results: Intrarater reliability was high (intraclass correlation coefficient [ICC] ≥0.99). The ICC for interrater reliability varied from 0.85 to 0.97. The ICC was low at 4 and 18 months CA. Conclusions: The AIMS is reliable in evaluating motor development in infants born preterm. Clinicians should be cautious about using the AIMS in infants at very young ages and those approaching independent ambulation. Accurate placement of the window on a movement repertoire is crucial. Attention is required when using the AIMS in infants developing atypically. This study of the AIMS reveals that the scale is reliable in evaluating motor development in infants born preterm. The authors caution clinicians when using the scale for infants at very young ages and those close to attaining independent ambulation and emphasize accurate placement of the window on a movement repertoire.

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 score0.012
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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

Citations29
Published2010
Admission routes1
Has abstractyes

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