They are not destined to fail: a systematic examination of scores on embedded performance validity indicators in patients with intellectual disability
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
This study was designed to determine the clinical utility of embedded performance validity indicators (EVIs) in adults with intellectual disability (ID) during neuropsychological assessment. Based on previous research, unacceptably high (>16%) base rates of failure (BRFail) were predicted on EVIs using on the method of threshold, but not on EVIs based on alternative detection methods. A comprehensive battery of neuropsychological tests was administered to 23 adults with ID (MAge = 37.7 years, MFSIQ = 64.9). BRFail were computed at two levels of cut-offs for 32 EVIs. Patients produced very high BRFail on 22 EVIs (18.2%-100%), indicating unacceptable levels of false positive errors. However, on the remaining ten EVIs BRFail was <16%. Moreover, six of the EVIs had a zero BRFail, indicating perfect specificity. Consistent with previous research, individuals with ID failed the majority of EVIs at high BRFail. However, they produced BRFail similar to cognitively higher functioning patients on select EVIs based on recognition memory and unusual patterns of performance, suggesting that the high BRFail reported in the literature may reflect instrumentation artefacts. The implications of these findings for clinical and forensic assessment are discussed.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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