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Record W2783722694 · doi:10.1111/ajag.12483

Frailty prevalence in Australia: Findings from four pooled Australian cohort studies

2018· article· en· W2783722694 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.

Bibliographic record

VenueAustralasian Journal on Ageing · 2018
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsDalhousie University
FundersNational Health and Medical Research Council
KeywordsMedicineCohortDemographyGerontologyMarital statusCohort studyAgeingOlder peopleFrailty IndexPopulationInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine frailty prevalence in Australian older adults. METHODS: Frailty was measured using a modified Fried Frailty Phenotype (FFP) in a combined cohort of 8804 Australian adults aged ≥65 years (female 86%, median age 80 (79-82) years) from the Dynamic Analyses to Optimise Ageing Project and the North West Adelaide Health Study. RESULTS: Using the FFP, 21% of participants were frail while a further 48% were prefrail. Chi-squared testing of frailty among four age groups (65-69, 70-74, 75-79 and 80-84 years) for sex, and marital status revealed that frailty was significantly higher for women (approximately double that of men), increased significantly with advancing age for both sexes, and was significantly higher for women who were widowed, divorced or never married. CONCLUSION: If frailty could be prevented or reversed, it would have an impact on a larger number of older people.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.082
GPT teacher head0.360
Teacher spread0.278 · 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