Autism Observation Scale for Infants: Systematic Review and Meta-Analysis in Samples at Increased Likelihood of Autism Spectrum Disorders
Bibliographic record
Abstract
The Autism Observation Scale for Infants (AOSI) is being applied to non infant sibling populations. Assessment of the tool's utility across increased likelihood (IL) populations is therefore needed. A systematic review and meta-analysis was conducted on 17 studies identified from six databases. The AOSI has been used in four IL contexts: infant siblings, infants with Fragile X Syndrome, Tuberous Sclerosis Complex, and Down Syndrome. There were three main findings: (1) five studies report classification data though no consistent approach was used; (2) group differences between IL-ASD, IL non-ASD, and controls started at 12-months; and (3) large effect sizes between IL-ASD and control samples was identified. Utility of the AOSI to identify early signs of ASD in IL populations was demonstrated. Supplementary Information: The online version contains supplementary material available at 10.1007/s40489-023-00417-y.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".