Introducing a forced-choice recognition task to the California Verbal Learning Test – Children’s Version
Why this work is in the frame
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Bibliographic record
Abstract
The importance of performance validity tests (PVTs) is increasingly recognized in pediatric neuropsychology. To date, research has focused on investigating whether PVTs designed for adults function similarly in children. The downward extension of adult cutoffs is counter-intuitive considering the robust effect of age-related changes in basic cognitive skills in children and adolescents. The purpose of this study was to examine the signal detection properties of a forced-choice recognition trial (FCR-C) for the California Verbal Learning Test - Children's Version. A total of 72 children aged 6-15 years (M = 11.1 , SD = 2.6) completed the FCR-C as part of a larger neuropsychological assessment battery. Cross-validation analyses revealed that the FCR-C had good signal detection performance against reference PVTs. The first level of failure (≤14/15) produced the best combination of overall sensitivity (.31) and specificity (.87). A more conservative FCR-C cutoff (≤13) resulted in a predictable trade-off between sensitivity (.15) and specificity (.94), but also a net loss in discriminant power. Lowering the cutoff to ≤12 resulted in a slight improvement in specificity (.97) but further deterioration in sensitivity (.14). These preliminary findings suggest that the FCR-C has the potential to become the newest addition to a growing arsenal of pediatric PVTs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 it