False-Positive Error Rates for Reliable Digit Span and Auditory Verbal Learning Test Performance Validity Measures in Amnestic Mild Cognitive Impairment and Early Alzheimer Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The objective is to examine failure on three embedded performance validity tests [Reliable Digit Span (RDS), Auditory Verbal Learning Test (AVLT) logistic regression, and AVLT recognition memory] in early Alzheimer disease (AD; n = 178), amnestic mild cognitive impairment (MCI; n = 365), and cognitively intact age-matched controls (n = 206). METHOD: Neuropsychological tests scores were obtained from subjects participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: RDS failure using a ≤7 RDS threshold was 60/178 (34%) for early AD, 52/365 (14%) for MCI, and 17/206 (8%) for controls. A ≤6 RDS criterion reduced this rate to 24/178 (13%) for early AD, 15/365 (4%) for MCI, and 7/206 (3%) for controls. AVLT logistic regression probability of ≥.76 yielded unacceptably high false-positive rates in both clinical groups [early AD = 149/178 (79%); MCI = 159/365 (44%)] but not cognitively intact controls (13/206, 6%). AVLT recognition criterion of ≤9/15 classified 125/178 (70%) of early AD, 155/365 (42%) of MCI, and 18/206 (9%) of control scores as invalid, which decreased to 66/178 (37%) for early AD, 46/365 (13%) for MCI, and 10/206 (5%) for controls when applying a ≤5/15 criterion. Despite high false-positive rates across individual measures and thresholds, combining RDS ≤ 6 and AVLT recognition ≤9/15 classified only 9/178 (5%) of early AD and 4/365 (1%) of MCI patients as invalid performers. CONCLUSIONS: Embedded validity cutoffs derived from mixed clinical groups produce unacceptably high false-positive rates in MCI and early AD. Combining embedded PVT indicators lowers the false-positive rate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it