Preventing Frailty Progression During the Covid-19 Pandemic
Bibliographic record
Abstract
High rates of SARS-CoV-2 infection and mortality in long term care (LTC) facilities epitomize the contextual and biological risk of those frail and vulnerable among us (1). Much ado has been given to the vulnerability of older adults during the COVID-19 pandemic, but this vulnerability likely has much more to do with the reduced physiological resilience inherent to frailty status rather than chronological age per se (2). While strict measures to protect those who are frail are warranted, without careful consideration, these strategies will lead many older adults out of the frying pan and into the fire. The harsh reality is many at-risk adults will face disproportionate social isolation, depression, malnutrition, reduced access to care, decreased physical activity, and increased sedentary time as a result of infection prevention measures. Therefore, even frail adults who do not contract COVID-19, will undoubtedly experience reduced quality of life, accelerated frailty progression and worse clinical outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".