Standards of diagnostic assessment for autism spectrum disorder
Bibliographic record
Abstract
The rising prevalence of autism spectrum disorder (ASD) has created a need to expand ASD diagnostic capacity by community-based paediatricians and other primary care providers. Although evidence suggests that some children can be definitively diagnosed by 2 years of age, many are not diagnosed until 4 to 5 years of age. Most clinical guidelines recommend multidisciplinary team involvement in the ASD diagnostic process. Although a maximal wait time of 3 to 6 months has been recommended by three recent ASD guidelines, the time from referral to a team-based ASD diagnostic evaluation commonly takes more than a year in many Canadian communities. More paediatric health care providers should be trained to diagnose less complex cases of ASD. This statement provides community-based paediatric clinicians with recommendations, tools, and resources to perform or assist in the diagnostic evaluation of ASD. It also offers guidance on referral for a comprehensive needs assessment both for treatment and intervention planning, using a flexible, multilevel approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".