Comparison of the predictive validity of the Alberta Infant Motor Scale and Infant Neurological International Battery in low-birth-weight infants: a prospective longitudinal study
Bibliographic record
Abstract
Introduction This study aims to test the predictive validity of the Infant Neurological International Battery (INFANIB) and the Alberta Infant Motor Scale (AIMS) against the Peabody Developmental Motor Scale-2 (PDMS-2) at 4, 8 and 12 months of age in low birth weight (LBW) infants. Methods Motor development in 18 LBW infants was examined prospectively at 4, 8 and 12 months. A professional investigator assessed the motor development of these infants using the AIMS, INFANIB and PDMS-2. The validity of the results was assessed using Friedman and Wilcoxon signed-rank tests on the total raw scores of PDMS-2, AIMS and INFANIB at the three distinct age points. The chi-square test was used to calculate the association between INFANIB and AIMS with PDMS-2 for normal and LBW infants at each age point. Results The INFANIB and AIMS scores were both associated with PDMS-2 at all three age points. However, INFANIB demonstrated a higher predictive validity for PDMS-2 in LBW infants than AIMS. Conclusions The INFANIB has greater predictive validity than AIMS for assessing motor outcomes in LBW infants at 4, 8 and 12 months.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".