Short-Form Prediction of WAIS-R Scores in a Sample of Individuals Diagnosed With Multiple Sclerosis
Bibliographic record
Abstract
A short form of the Wechsler Adult Intelligence Scale--Revised (WAIS-R) developed by Ward (WAIS-R/7 SF; 1990) was used to generate Verbal, Performance, and Full Scale IQ scores (VIQ, PIQ, and FSIQ, respectively) in 66 individuals diagnosed with multiple sclerosis (MS). Short-form scores were highly correlated with WAIS-R scores. However, the short-form VIQ and PIQ, but not FSIQ, scores differed significantly from corresponding WAIS-R scores. WAIS-R/7 SF VIQ, PIQ, and FSIQ scores fell within 5, 9, and 6 absolute error points, respectively, of corresponding WAIS-R IQ scores in 95% of cases. Classification of IQ scores into ranges (e.g., average, high average, etc.) based on the scheme outlined by Wechsler (1981) was consistent between WAIS-R/7 SF and WAIS-R scores in 81.8% (for VIQ), 74.8% (for PIQ), and 89.4% (for FSIQ) of cases. These findings are discussed within the context of using the WAIS-R/7 SF in the assessment of MS patients.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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; 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".