Bibliographic record
Abstract
* Abbreviations: ASD — : autism spectrum disorder M-CHAT/F — : Modified Checklist for Autism in Toddlers With Follow-up PPV — : positive predictive value The lengthy diagnostic odyssey experienced by families of children with autism spectrum disorder (ASD) remains a major barrier to early access to ASD therapeutic services. Although accelerating this process has been identified as a top priority,1 there is a polarized debate about whether ASD screening can accomplish this. The American Academy of Pediatrics recommends that all children be assessed by using an ASD screening tool at 18 and 24 months old.2 In contrast, the US Preventive Services Task Force concluded that there was “insufficient evidence to recommend screening for ASD in children aged 18 to 30 months for whom no concerns of ASD have been raised.”3 The issue has been debated passionately,4–6 but without resolution, in part because of limited community-level data regarding screening feasibility, accuracy, and outcomes. The current study by Guthrie et al7 contributes important findings that further inform this debate. The authors demonstrated that universal screening was feasible, with >90% of toddlers screened through a large primary care network by integrating the Modified Checklist for Autism in Toddlers (M-CHAT) With Follow-up (M-CHAT/F) into routine primary health care. Physicians were prompted to administer the … Address correspondence to Lonnie Zwaigenbaum, MD, MSc, Autism Research Centre, Glenrose Rehabilitation Hospital, University of Alberta, E209, 10230 111th Ave, Edmonton, AB T5G 0B7, Canada. E-mail: lonniez{at}ualberta.ca
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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 | 0.014 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.018 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.035 | 0.012 |
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".