Development of demographic norms for four new WAIS-III/WMS-III indexes.
Bibliographic record
Abstract
Following the publication of the third edition Wechsler scales (i.e., WAIS-III and WMS-III), demographically corrected norms were made available in the form of a computerized scoring program (i.e., WAIS-III/WMS-III/WIAT-II Scoring Assistant). These norms correct for age, gender, ethnicity, and education. Since then, four new indexes have been developed: the WAIS-III General Ability Index, the WMS-III Delayed Memory Index, and the two alternate Immediate and Delayed Memory Indexes. The purpose of this study was to develop demographically corrected norms for the four new indexes using the standardization sample and education oversample from the WAIS-III and WMS-III. These norms were developed using the same methodology as the demographically corrected norms made available in the WAIS-III/WMS-III/WIAT-II Scoring Assistant.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".