Bibliographic record
Abstract
At present, frailty is defined variably. Some consensus on a definition is likely to emerge, but the basis for a successful definition needs to be explored. Here, a classic approach to validation is proposed: a successful definition of frailty should be multifactorial but must also manage the many factors in a way that takes their interactions into account. It is likely to be correlated with disability, co-morbidity and self-rated health, and should identify a group that is vulnerable to adverse outcomes. Ideally, it should also be susceptible to animal modelling. In that frailty and age are so bound together, it is also likely that there will be some age at which virtually all people will be frail, by any definition. Apart from being valid, the success of any definition of frailty will depend on it being useful to researchers and clinicians. The need for progress on our understanding of frailty is evident, but for now, there is insufficient evidence to accept a single definition of frailty.
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 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 | 0.065 | 0.152 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.009 | 0.020 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".