Failing Performance Validity Cutoffs on the Boston Naming Test (BNT) Is Specific, but Insensitive to Non-Credible Responding
Bibliographic record
Abstract
This study was designed to examine alternative validity cutoffs on the Boston Naming Test (BNT).Archival data were collected from 206 adults assessed in a medicolegal setting following a motor vehicle collision. Classification accuracy was evaluated against three criterion PVTs.The first cutoff to achieve minimum specificity (.87-.88) was T ≤ 35, at .33-.45 sensitivity. T ≤ 33 improved specificity (.92-.93) at .24-.34 sensitivity. BNT validity cutoffs correctly classified 67-85% of the sample. Failing the BNT was unrelated to self-reported emotional distress. Although constrained by its low sensitivity, the BNT remains a useful embedded PVT.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".