Predicting Age of Independent Walking in Preterm Infants: A Longitudinal Study Using Neonatal Characteristics and Motor Development Variables
Bibliographic record
Abstract
OBJECTIVE: To formulate an equation estimating months to independent walking in moderate to late preterm infants based on neonatal characteristics and gross motor development from 7 months to independent walking. METHODS: Sixty infants born between 32 to 36 weeks were assessed using Alberta Infant Motor Scale (AIMS) for gross motor development. Neonatal characteristics were recorded at 7 months, and caregiver-reported independent walking onset. Pearson correlation analyzed age, AIMS scores, and neonatal factors. Multiple regression developed the prediction equation. RESULTS: The equation for independent walking onset, which included gestational age (GA) at birth, total AIMS score at 10 months of age (10th AIMS), and birth head circumference (BHC), exhibited a strong correlation (r=0.707) and had a predictive power of 50.0%. The equation is as follows: age onset of independent walking (months)=33.157, -0.296 (GA), -0.132 (10th AIMS), -0.196 (BHC), with an estimation error of 0.631 months. CONCLUSION: Neonatal characteristics, such as GA, 10th AIMS, and BHC, are key determinants in estimating the onset of independent walking in moderate to late preterm infants.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".