VARIABILITY IN NEUROPHYSIOLOGICAL AND NEUROPSYCHOLOGICAL FUNCTION: NOVEL INSIGHTS IN COGNITIVE AGING
Bibliographic record
Abstract
Intraindividual variability (IIV) in cognitive behavioural performance has emerged as a complementary perspective to central tendency for indexing central nervous system function in general, and neurodegenerative dysfunction in particular. The merits of this IIV approach have been demonstrated consistently in terms of response time inconsistency on speeded tasks; however, recent research employing functional neuroimaging and neuropsychological assessment has demonstrated additional novel applications of this variability lens. For example, greater neural variability may reflect a more agile and adaptive nervous system capable of responding within a greater dynamic range, with our own work showing that increased neural variability aligns with better performance on executive functioning tasks. IIV in neuropsychological functioning computed across multiple tests within a battery predicts greater incidence of dementia, with our own work demonstrating links between dispersion and white matter integrity. On balance, IIV in neurophysiological and neuropsychological functioning holds promise for furthering our understanding of cognitive aging.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".