Settling the Score: Can CPT-3 Embedded Validity Indicators Distinguish Between Credible and Non-Credible Responders Referred for ADHD and/or SLD?
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to further investigate the clinical utility of individual and composite indicators within the CPT-3 as embedded validity indicators (EVIs) given the discrepant findings of previous investigations. METHODS: = 42) groups based on five criterion measures. RESULTS: Receiver operating characteristic curves (ROC) revealed that 5/9 individual indicators and 2/4 composite indicators met minimally acceptable classification accuracy of ≥0.70 (AUC = 0.43-0.78). Individual (0.16-0.45) and composite indicators (0.23-0.35) demonstrated low sensitivity when using cutoffs that maintained specificity ≥90%. CONCLUSION: Given the lack of stability across studies, further research is needed before recommending any specific cutoff be used in clinical practice with individuals seeking psychoeducational assessment.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".