Investigation of the relationship between gross motor maturation from 1 to 18 months and preschool gross motor performance in at‐risk infants
Bibliographic record
Abstract
BACKGROUND: At-risk infants are predisposed to major and minor neurodevelopmental disorders due to various biological and environmental factors. OBJECTIVE: This study aimed to investigate the relationship between gross motor maturation from 1 to 18 months and gross motor performance in the preschool period, as well as the risk of developmental coordination disorder (DCD) in at-risk infants, referred to the Family Counselling Center of the Turkish Spastic Children's Foundation (FCCTSCF) between 2014 and 2016. METHODS: Fifty-seven children who had their gross motor maturation assessed between 1 and 18 months at the FCCTSCF were re-evaluated in the preschool period. The Alberta Infant Motor Scale (AIMS) was used to evaluate gross motor maturation between 1 and 18 months. In contrast, the Gross Motor Function Measure-88 and the Developmental Coordination Disorder Questionnaire were used to assess gross motor performance in the preschool period. RESULTS: Of the at-risk infants included in the study, 45.6% were evaluated as having typical development, 21% were identified as having cerebral palsy (CP), and 33.3% were determined to be at risk for DCD. Children with CP and those at risk for DCD were found to have lower percentile ranks on the past AIMS test compared to the healthy group (p = 0.001). A significant positive correlation was found between the Alberta Infant Motor Scale and the Gross Motor Function Measure-88 (p = 0.014). CONCLUSION: In the clinical follow-up of at-risk infants, those who scored low on AIMS should be monitored for future risk of DCD and minor disorders, even if major neurological issues such as cerebral palsy are not detected.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".