IDENTIFICATION OF RISK FACTORS FOR MORTALITY AND LOW QUALITY OF LIFE SURVIVAL IN FRAIL OLDER WOMEN
Bibliographic record
Abstract
for model confirmation. Frailty and cognitive impairment were measured using a deficit accumulation approach. Cross-lagged path analysis within a structural equation modelling (SEM) framework was used to examine the bi-directional relationship between the two measures. Results: Each additional frailty deficit at Time1 was associated with a 0.02 increase in cognitive deficits at Time 2, p<.001, controlling for age, gender, social vulnerability, education and initial frailty and cognitive impairment. Likewise, each additional cognitive deficit at Time 1 was associated with a 0.32 increase in frailty deficits at Time 2, p<.01. Discussion: This reciprocal relationship could lead to downward spirals in health with increasing frailty leading to more cognitive impairment and vice versa. Whether interventions targeting either frailty or cognitive impairment could help prevent declines in the other remains a question for further research.
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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 | 0.003 | 0.002 |
| 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) | 0.000 | 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; a candidate call from one teacher head, 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".