A.2 Understanding Grit in healthy older adults at-risk for Alzheimer’s disease
Bibliographic record
Abstract
Background: Adherence to healthy lifestyle behaviours or to prescribed medication requires perseverance with stamina, and this is captured by Grit, a non-cognitive trait defined as perseverance and passion for long-term goals. Despite predicting cognitive decline and physical, emotional, and social functioning, Grit remains poorly understood and its neural substrates are unknown in cognitive aging. Methods: Ninety-five cognitively unimpaired older adults with a family history of Alzheimer’s disease were recruited through the PREVENT-AD longitudinal cohort. Participants completed tests that assess grit and conscientiousness and underwent resting-state functional magnetic resonance imaging (fMRI). Multivariate pattern analyses (MVPA), a rigorous data-driven whole-brain approach, were used to examine if resting-state functional connectivity of connectome-wide voxels were associated with grit scores, controlling for age, sex, APOE ε4 carriership, mean displacement, and conscientiousness. Results: Our analyses identified two large (≥54 voxels) and statistically significant (p<0.01 corrected for family-wise error) clusters in the right ventrolateral prefrontal cortex and the left orbitofrontal cortex underlying grit. Conclusions: Being the first to identify functional neural correlates supporting grit in the aging population while accounting for the variance of conscientiousness, our study provides unique insights into the construct which has important applications in adherence to clinical and empirical neurological interventions as well as in successful aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".