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Record W2731460737 · doi:10.1093/geroni/igx004.2585

CLINICAL AND HEALTHCARE OUTCOMES OF ASSISTED LIVING RESIDENTS: A CANADIAN PERSPECTIVE

2017· article· en· W2731460737 on OpenAlexaffabout
Colleen J. Maxwell, David B. Hogan, Joseph Emmanuel Amuah, Laurel A. Strain

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of OttawaCanadian Institute for Health InformationUniversity of AlbertaUniversity of CalgaryUniversity of Waterloo
Fundersnot available
KeywordsStaffingResidenceMedicineIncidence (geometry)Health careGerontologyAged careLong-term careCohortEpidemiologyFamily medicineNursingEnvironmental healthDemography

Abstract

fetched live from OpenAlex

Assisted living (AL) has emerged as a popular residential care option for older adults in Canada. Similar to the U.S. experience, its introduction has raised concerns about regulatory oversight, eligibility criteria, staffing levels and quality of care. The Alberta Continuing Care Epidemiological Studies (ACCES) is the first prospective cohort study in Canada to examine AL residents’ health and social needs and healthcare outcomes. ACCES included 1,089 older (65+) residents from 59 AL residences and 1,000 residents from 54 nursing homes (NHs) across Alberta. In both settings, dementia was the most common diagnosis (58% AL, 71% NH). Despite being less impaired, AL residents exhibited an annual incidence of hospitalization 3-times higher than NH residents (38.9% vs. 13.7%). They also showed an annual incidence of NH placement of 18.3%. Key drivers of both outcomes included AL resident characteristics (health and social vulnerability) and residence factors (size, staffing levels and oversight).

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)0.002
metaresearch head score (Gemma)0.005
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 score0.070
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.010
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.124
GPT teacher head0.502
Teacher spread0.378 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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