Exploring effects of type 2 diabetes on cognitive functioning in older adults.
Bibliographic record
Abstract
Type 2 diabetes may be associated with exacerbated aging-related declines in cognitive neuropsychological performance. The authors examined whether such effects are systematic (i.e., broadly distributed across domains or domain-specific) or moderated by age (i.e., varying across age within older adults). The authors assembled recent cross-sectional data from the Victoria Longitudinal Study (VLS) Sample 3 (Wave 1; initial n = 570; initial age = 53-90 years). Using a comprehensive, multidimensional spectrum of cognitive neuropsychological tests, the authors examined performance differences by diabetes status (diabetes group vs. healthy controls) and age (young-old vs. old-old). Our results showed that healthy controls significantly outperformed the diabetes group only on markers of executive functioning and speed. Notably, the diabetes-related effects were robust across the two late-life age groups. Future research examining longitudinal changes is recommended.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".