Estimating Premorbid General Cognitive Functioning for Children and Adolescents Using the American Wechsler Intelligence Scale for Children—Fourth Edition: Demographic and Current Performance Approaches
Bibliographic record
Abstract
Neuropsychologic evaluation requires current test performance be contrasted against a comparison standard to determine if change has occurred. An estimate of premorbid intelligence quotient (IQ) is often used as a comparison standard. The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is a commonly used intelligence test. However, there is no method to estimate premorbid IQ for the WISC-IV, limiting the test's utility for neuropsychologic assessment. This study develops algorithms to estimate premorbid Full Scale IQ scores. Participants were the American WISC-IV standardization sample (N = 2172). The sample was randomly divided into 2 groups (development and validation). The development group was used to generate 12 algorithms. These algorithms were accurate predictors of WISC-IV Full Scale IQ scores in healthy children and adolescents. These algorithms hold promise as a method to predict premorbid IQ for patients with known or suspected neurologic dysfunction; however, clinical validation is required.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".