Diagnostic Assessment of Autism Spectrum Disorder: A Cross-Disciplinary Analysis
Bibliographic record
Abstract
To date, there are no known biological markers to diagnose Autism Spectrum Disorder (ASD). Thus, diagnosis generally relies on behavioural assessment and considerable clinical judgement. Currently, very little is known about the assessment methodology Canadian physicians and psychologists use, to diagnose ASD. The current study provides information regarding these practices. A total of 64 participants (23 physicians and 41 psychologists) completed an online survey. Overall, the participants reported a relatively homogenous set of assessment practices. Small differences were noted in the usage of some assessment tools and in the composition of their clinical team. Assessment tool usage differed depending on the estimated cognitive level of the client population a clinician worked with. Limitations and future directions for the research are discussed. It is hoped that these results will help promote further research into the clinical practice of diagnosticians working with children diagnosed with (or being assessed for) ASD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".