Accuracy of the Alberta Infant Motor Scale (AIMS) to detect developmental delay of gross motor skills in preterm infants: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To assess, through a systematic review, the ability of Alberta Infant Motor Scale (AIMS) to diagnose delayed motor development in preterm infants. METHODS: Systematic searches identified five studies meeting inclusion criteria. These studies were evaluated in terms of: participants' characteristics, main results and risk of bias. The risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies--second edition (QUADAS-2). RESULTS: All five studies included a high risk of bias in at least one of the assessed fields. The most frequent biases included were presented in patient selection and lost follow up. All studies used the Pearson correlation coefficient to assess the diagnostic capability of the Alberta Infant Motor Scale. None of the assessed studies used psychometric measures to analyze the data. CONCLUSION: Given the evidence, the research supporting the ability of Alberta Infant Motor Scale to diagnose delayed motor development in preterm infants presents limitations. Further studies are suggested in order to avoid the above-mentioned biases to assess the Alberta Infant Motor Scale accuracy in preterm babies.
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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 | 0.012 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".