Bibliographic record
Abstract
OBJECTIVE: To review existing data on early signs of autistic spectrum disorders (ASD) and on how these disorders can be distinguished from other atypical patterns of development, and to describe a developmental surveillance approach that family physicians can use to ensure that children with these diagnoses are detected as early as possible. QUALITY OF EVIDENCE: MEDLINE was searched from January 1966 to July 2000 using the MeSH terms autistic disorder/diagnosis AND diagnosis, differential AND (infant OR child, preschool). Articles were selected based on relevance to developmental surveillance in primary care and on experimental design, with emphasis on prospective studies with systematic measurement procedures using up-to-date diagnostic criteria. MAIN MESSAGE: Autistic spectrum disorders are characterized by impairments in social interaction and verbal and nonverbal communication, and by preferences for repetitive interests and behaviours. Early signs that distinguish ASD from other atypical patterns of development include poor use of eye gaze, lack of gestures to direct other people's attention (particularly to show things of interest), diminished social responsiveness, and lack of age-appropriate play with toys (especially imaginative use of toys). Careful attention to parents' concerns and specific inquiry into and observation of how children interact, communicate, and play will help ensure that early signs are detected during regular health maintenance visits. CONCLUSION: Family physicians have an important role in early identification of children with ASD. Early diagnosis of these disorders is essential to ensure timely access to interventions known to improve outcomes for these children.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".