Establish normative value of Alberta infant motor scale in Pune population
Bibliographic record
Abstract
Background: The Alberta infant motor scale (AIMS) is a norm-reference test that assessed the spontaneous motor performance of infant 0-18 month. AIMS is development, motor assessment tools in the evaluation of motor risk in infants, but this scale was formulated by using western samples. In every country various differences are observed in the culture and ethnicity. Therefore, there is a need to establish normative value of AIMS in Pune population. Aim of the study was to establish normative value of AIMS in Pune population.Methods: A descriptive one time study of 420 healthy infants aged between 0 to 18 months was included in the study. Infants were observed in prone, supine, sitting, and standing positions. Infants were measured using the AIMS test and represent normative value in Pune population.Results: Medcalc software was used for the statistical analysis. For each month we calculated the mean AIMS score, and standard deviation, as well as percentiles. Results showed increases in raw scores across age groups from 0 to 15 months of age. The stability of raw scores was observed after 16 months of age. Pune infants demonstrated lower scores in specific ages compared to the Canadian sample.Conclusions: Although the AIMS is used in both research and clinical practice, it has certain limitations in terms of behavioral differentiation before 2 months and after 15 months. This reduced sensitivity at the extremes of the age range may be related to the number of motor items assessed at these ages’ 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".