Clinical Validation of Canadian WAIS-III Index Short Forms in Inpatient Neuropsychiatry and Forensic Psychiatry
Bibliographic record
Abstract
Recent research has provided some support for the concurrent validity of two-subtest short forms for estimating Canadian WAIS-III Index scores in the standardization sample (Lange & Iverson, in press). The purpose of this study was to examine the efficacy of using various two-subtest short forms to estimate Canadian WAIS-III Index scores in a clinical population. Participants were 100 inpatients from two large psychiatric hospitals in British Columbia, Canada. Using all possible two-subtest combinations, estimated VCI, POI, and WMI scores were generated by prorating subtest scaled scores and using the Canadian normative data (Wechsler, 2001). The agreement rate between full form and short form index scores was very high for all subtest combinations (range = 90-98%). Two-subtest short forms were useful for estimating VCI, POI, and WMI scores in this population.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".