Frailty: An Emerging Research and Clinical Paradigm--Issues and Controversies
Bibliographic record
Abstract
Clinicians and researchers have shown increasing interest in frailty. Yet, there is still considerable uncertainty regarding the concept and its definition. In this article, we present perspectives on key issues and controversies discussed by scientists from 13 different countries, representing a diverse range of disciplines, at the 2006 Second International Working Meeting on Frailty and Aging. The following fundamental questions are discussed: What is the distinction, if any, between frailty and aging? What is its relationship with chronic disease? Is frailty a syndrome or a series of age-related impairments that predict adverse outcomes? What are the critical domains in its operational definition? Is frailty a useful concept? The implications of different models and approaches are examined. Although consensus has yet to be attained, work accomplished to date has opened exciting new horizons. The article concludes with suggested directions for future research.
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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 | 0.035 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".