Cognition assessment using the NIH Toolbox
Bibliographic record
Abstract
Cognition is 1 of 4 domains measured by the NIH Toolbox for the Assessment of Neurological and Behavioral Function (NIH-TB), and complements modules testing motor function, sensation, and emotion. On the basis of expert panels, the cognition subdomains identified as most important for health, success in school and work, and independence in daily functioning were Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention. Seven measures were designed to tap constructs within these subdomains. The instruments were validated in English, in a sample of 476 participants ranging in age from 3 to 85 years, with representation from both sexes, 3 racial/ethnic categories, and 3 levels of education. This report describes the development of the Cognition Battery and presents results on test-retest reliability, age effects on performance, and convergent and discriminant construct validity. The NIH-TB Cognition Battery is intended to serve as a brief, convenient set of measures to supplement other outcome measures in epidemiologic and longitudinal research and clinical trials. With a computerized format and national standardization, this battery will provide a "common currency" among researchers for comparisons across a wide range of studies and populations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".