MétaCan
Menu
Back to cohort

Counting Backward to Health Care's Future: Using Time‐to‐Death Modeling to Identify Changes in End‐of‐Life Morbidity and the Impact of Aging on Health Care Expenditures

2007· review· en· W1984623892 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMilbank Quarterly · 2007
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of Toronto
FundersCanadian Health Services Research Foundation
KeywordsGerontologyHealth carePopulation ageingMedicinePopulationEnvironmental healthEconomicsEconomic growth

Abstract

fetched live from OpenAlex

In most developed countries, as the largest population cohorts approach the age of sixty-five, the impact of population aging on health care expenditures has become a topic of growing interest. This articles examines trends in elderly disability and end-of-life morbidity, estimations of the cost of dying, and models of expenditures as a function of both age and time-to-death and finds broad improvement in mortality and morbidity among the elderly in the developed world. Reduced mortality and low growth in the costs associated with dying could reduce forecasted expenditures, but high growth in expenditures for those not close to death and for nonhospital services could create new economic pressures on health care systems.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.135
GPT teacher head0.528
Teacher spread0.394 · 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