Ecological Validity of the WMS-III Rarely Missed Index in Personal Injury Litigation
Bibliographic record
Abstract
The purpose of this study was to evaluate the clinical utility of the Rarely Missed Index (RMI) to detect cognitive exaggeration in 78 nonlitigant patients (i.e., Mixed Clinical group) and 158 personal injury litigants (i.e., 20 Suspected Exaggerators, 12 Borderline Exaggerators, 126 Genuine Responders). The base rate for probable malingered neurocognitive dysfunction in the litigant sample was 12.7%. The false positive error rate of the RMI in the Genuine Responder and Mixed Clinical group ranged from 5.4% to 8.6%. Positive RMI scores were found in 25% and 41.7% of the Suspected Exaggerator and Borderline Exaggerator groups respectively. The clinical utility of the RMI to identify Suspected Exaggerators versus individuals in the Genuine Responder and Mixed Clinical groups revealed low sensitivity (sensitivity = .25), very high specificity (range = .91 to .95), moderate positive predictive power (range = .50 to .71), and moderate to high negative predictive power (range = .68 to .83). These results do not support the use of the RMI as a reliable predictor of cognitive exaggeration.
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.
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 | 0.001 |
| 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 | 0.001 |
| 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".