Enabling Healthy Aging to AVOID Frailty in Community Dwelling Older Canadians
Bibliographic record
Abstract
The Canadian population is aging. With aging, biological and social changes occur increasing the risk of developing chronic conditions and functional loss leading to frailty. Older adults living with frailty are more vulnerable to minor stressors, take longer to recover from illness, and have difficulty participating in daily activities. The Canadian Frailty Network's (CFN) mission is to improve the lives of older adults living with frailty. In September 2019, CFN launched the Activity & Exercise, Vaccination, Optimization of medications, Interaction & Socialization, and Diet & Nutrition (AVOID) Frailty public health campaign to promote assessing and reducing risk factors leading to the development of frailty. As part of the campaign, CFN held an Enabling Healthy Aging Symposium with 36 stakeholders from across Canada. Stakeholders identified individual and community-level opportunities and challenges for the enablement of healthy aging and frailty mitigation, as part of a focused consultative process. Stakeholders ranked the three most important challenges and opportunities at the individual and community levels for implementing AVOID Frailty recommendations. Concrete actions, further research areas, policy changes, and existing resources/programs to enhance the AVOID Frailty campaign were identified. The results will help inform future priorities and behaviour change strategies for healthy aging in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 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".