Linking Stable and Dynamic Features of Positive Affect to Sleep
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Poor sleep contributes to adult morbidity and mortality. PURPOSE: The study examined the extent to which trait positive affect (PA) and PA reactivity, defined as the magnitude of change in daily PA in response to daily events, were linked to sleep outcomes. METHODS: Analyses are based on data from 100 respondents selected from the National Survey of Midlife in the United States. RESULTS: Multilevel analyses indicated that higher levels of trait PA were associated with greater morning rest and better overall sleep quality. In contrast, PA reactivity was associated with diminished sleep efficiency. Finally, interactions between PA reactivity and trait PA emerged on all three sleep measures, such that higher event-related change in daily positive affect was associated with impaired sleep, especially among individuals high in trait PA. CONCLUSIONS: Results suggest that high trait PA, when coupled with high PA reactivity, may contribute to poor sleep.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it