Bibliographic record
Abstract
OBJECTIVE: The present study investigated the validity of using the Conners' Teacher and Parent Rating Scales (CTRS/CPRS) or semistructured diagnostic interviews (Parent Interview for Child Symptoms and Teacher Telephone Interview) to predict a best-practices clinical diagnosis of ADHD. METHOD: A total of 279 children received a clinical diagnosis based on a best-practices comprehensive assessment (including diagnostic parent and teacher interviews, collection of historical information, rating scales, classroom observations, and a psychoeducational assessment) at a specialty ADHD Clinic in Truro, Nova Scotia, Canada. Sensitivity and specificity with clinical diagnosis were determined for the ratings scales and diagnostic interviews. RESULTS: Sensitivity and specificity values were high for the diagnostic interviews (91.8% and 70.7%, respectively). However, while sensitivity of the CTRS/CPRS was relatively high (83.5%), specificity was poor (35.7%). CONCLUSION: The low specificity of the CPRS/CTRS is not sufficient to be used alone to diagnose ADHD. (J. of Att. Dis. 2016; 20(6) 478-486).
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 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".