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Record W2044600197 · doi:10.3109/09638280903168515

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

2009· article· en· W2044600197 on OpenAlexaff
Keith C. Hayes, Dalton L. Wolfe, Steven A. Trujillo, Jacquelyn Burkell

Bibliographic record

VenueDisability and Rehabilitation · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsWestern UniversityParkwood Institute
Fundersnot available
KeywordsScope (computer science)Computer sciencePsychologyCognitive psychology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.319
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2009
Admission routes1
Has abstractyes

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