Intra-and inter-examiner reliability of Alberta Infant Motor Scale application in follow-up ambulatory of at-risk newborns
Bibliographic record
Abstract
ABSTRACT Prematurity is a risk factor for delayed motor development, and it is recommended to monitor these infants in the first two years of life. To verify the properties of intra and inter-examiner measurements of AIMS in an outpatient follow-up clinic for newborns at risk in a public maternity hospital. Prospective study conducted in an outpatient follow-up of high-risk newborns. The Intraclass Correlation Coefficient (ICC) was used to analyze reliability. To compare the intra-examiner evaluations, the paired T-test or Wilcoxon test was performed. The independent T-test was used to compare inter-examiner assessments. The correlation between variables was analyzed using the Pearson or Spearman test. The Bland Altman test was performed to assess the concordance between the scores. 31 preterm infants with 8,47 ± 4,49 of corrected age were evaluated. There was no significant difference between the evaluations intra and inter-examiner. The ICC values remained above 0.88 for both intra and inter-examiner evaluation. The scores showed high agreement. AIMS has intra- and inter-examiner reliability for assessing and monitoring preterm newborns for up to 18 months in a follow-up clinic.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".