On the interaction of disability and aging: Accelerated degradation models and their influence on projections of future care needs and costs for personal injury litigation
Bibliographic record
Abstract
PURPOSE: Accelerated degradation models are emerging as ways to characterize the interaction between disability and the functional decline of aging and to provide insights about the processes of aging with disability. Typically the models employ sophisticated mathematical treatments that are beyond the scope of many clinicians, lawyers, and others who might benefit from the information they contain. The purpose of this report is to characterize some rudimentary features of the models, in more readily understandable language, and illustrate how understanding of the underlying constructs can influence decisions regarding resource allocation and other projections of future care needs. METHODS: A literature review of longitudinal aging and disability studies was completed and simplified mathematical modeling undertaken, with hypothetical data, to illustrate various outcomes of the interaction of disability with the functional decline of aging. A specific example, drawn from personal injury litigation, i.e. projection of future care costs, was used to illustrate the practical applicability of this conceptual model. CONCLUSION: Awareness of the accelerated functional decline brought about by the superimposition of age-related functional losses on pre-existing disability reveals a need to provide for aids and personnel supports at an earlier age than might be expected because of the multiplicative interaction and the inadequacy of functional reserves to compensate for the disability.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".