Successful Aging and Frailty: Mutually Exclusive Paradigms or Two Ends of a Shared Continuum?
Bibliographic record
Abstract
The conceptualization of positive and negative states of aging is contentious at the inter- and intraparadigm level; lack of consensus exists within and between states. Working within their respective paradigms, successful aging and frailty researchers may have lost sight of the larger picture. Are successful aging researchers describing nonfrail individuals? Are frailty researchers describing unsuccessful aging? It is imperative that researchers are cognizant of the ways in which their perspectives are contextualized within the literature and within related paradigms, so as to be able to clearly communicate their research and to ensure they are working within the appropriate paradigm to facilitate desired outcomes. Here we discuss the similarities and differences between successful aging and frailty in terms of the scope and emphasis of their constituent components and functioning: both SA and frailty include biomedical components; SA examines the high end, whilst frailty predominately examines the low end of the functioning spectrum. Frailty models emphasize the biomedical realm, whilst SA models emphasize both the biomedical and the psychosocial.
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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 | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.072 |
| Scholarly communication | 0.016 | 0.037 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.005 | 0.015 |
| 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".