WMS–III performance in patients with temporal lobe epilepsy: Group differences and individual classification
Bibliographic record
Abstract
The utility of the WMS-III in detecting lateralized impairment was examined in a large sample of patients with temporal lobe epilepsy. Methods of analysis included evaluation of group means on the various indexes and subtest scores, the use of ROC curves, and an examination of Auditory-Visual Index discrepancy scores. In addition, performance on immediate and delayed indexes in the auditory and the visual modality was compared within each group. Of the WMS-III scores, the Auditory-Visual Delayed Index difference score appeared most sensitive to side of temporal dysfunction, although patient classification rates were not within an acceptable range to have clinical utility. The ability to predict laterality based on statistically significant index score differences was particularly weak for those with left temporal dysfunction. The use of unusually large discrepancies led to improved prediction, however, the rarity of such scores in this population limits their usefulness. Although the utility of the WMS-III in detecting laterality may be limited in preoperative cases, the WMS-III may still hold considerable promise as a measure of memory in documenting baseline performance and in detecting those that may be at risk following surgery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".