Examining referral patterns and diagnostic rates in the British Columbia autism assessment network
Bibliographic record
Abstract
Materials/Methods: Early Child Development was measured by the Child Development Evaluation (CDE) test, which is a screening tool developed and validated in Mexican population for children aged from 1 to 59 months, CDE results are expressed in a traffic light system as the following: green stands for normal development, yellow stands for development gap, red stands for risk of developmental delay.Child exposure to the early child care facility was divided in <30 days, 1 to 5 months, 6 to 11 months, 12 to 17 months, 18 to 23 months and >24 months.Variables are expressed in absolute frequency and percentage.Prevalence Odds Ration was obtained to look for associations for time and early child development level.Logistic Regression was obtained for normal early development probability.Statistic significance was established at p<0.05.SPSS 20.0 was used for statistic analysis.Results: The study included 3387 children from 177 EEP nurseries.53% were male; age by group was divided in 12-24 months (22.3%), 25-36 months (37.6%) and 37-42 months (40.1%).Normal development adjusted OR by age was 1.9 (CI95%: 1.30-2.78)6-11 months, 2.36 (95%IC: 1.60-3.50)for 12-17 months, 2.78 (95%IC: 1.65-4.65)for 18-23 months and 3.46 (95%IC: 2.13-5.60)for >24 months.By development area, a greater probability of having a normal result for language and social areas was observed after 6 months in the program, and for motor (both gross and fine) and knowledge areas after 12 months.Conclusions/Significance: Length of stay in the EEP after six months significantly and progressively increases the probability of normal development regardless of gender and age.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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 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".