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Record W207504271

Loss and recovery of independence among seniors.

2002· article· en· W207504271 on OpenAlexaffabout
Laurent Martel, Alain Bélanger, Jean‐Marie Berthelot

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsIndependence (probability theory)MedicineGerontologyLogistic regressionPopulation healthOddsPopulationDemographySocioeconomic statusChronic bronchitisEnvironmental healthStatisticsInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This article identifies risk factors associated with the loss and recovery of independence among the household population aged 65 or older. DATA SOURCES: The data are from the longitudinal component of the first two cycles (1994/95 and 1996/97) of Statistics Canada's National Population Health Survey (NPHS). Supplementary information is from the cross-sectional component of the 1998/99 NPHS. ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate the proportions of seniors who lost or regained independence between 1994/95 and 1996/97. Logistic regression models were used to explore associations between loss or recovery of independence and demographic, behavioural and socioeconomic variables, as well as chronic conditions. MAIN RESULTS: Age, sex and the effects of stroke were significantly related to the loss and recovery of independence among seniors. Bronchitis/emphysema, diabetes, heart disease, weight, physical activity, education and household income were associated with the loss of independence, but not its recovery. Dependent seniors with back problems, urinary incontinence, or who smoked had low odds of regaining independence.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.264
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2002
Admission routes2
Has abstractyes

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