MétaCan
Menu
Back to cohort
Record W2075256864 · doi:10.1155/2010/503817

Recent Visual Decline—A Health Hazard with Consequences for Social Life: A Study of Home Care Clients in 12 Countries

2010· article· en· W2075256864 on OpenAlexaffabout
Else Vengnes Grue, Harriet Finne‐Soveri, Paul Stolee, Jeff Poss, Liv Wergeland Sørbye, Anja Noro, John P. Hirdes, Anette Hylen Ranhoff

Bibliographic record

VenueCurrent Gerontology and Geriatrics Research · 2010
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Waterloo
FundersDiakonhjemmet HøgskoleDiakonhjemmetNorges BlindeforbundEuropean Commission
KeywordsAlgorithmArtificial intelligenceMedicineComputer scienceMachine learningDatabase

Abstract

fetched live from OpenAlex

Information about recent visual decline (RVD) and its consequences is limited. The aim was to investigate this in an observational, prospective study. Participants were recipients of community home services, >/=65 years, from Ontario (Canada, n = 101618), Finland (the-RAI-database, STAKES, n = 1103), and 10 other European countries (the-Aged-in-HOmeCarestudy (AdHOC), n = 3793). The instrument RAI-HC version 2.0 was used in all sites. RVD was assessed by the item "Worsening of vision compared to status 90 days ago" and was present in 6-49% in various sites, more common among persons living alone, and in females. In the AdHOC sample, RVD was independently associated with declining social activity and limited outdoors activities due to fear of falling. The combination of stable vision impairment (SVI) and RVD was independently associated with IADL loss. RVD is common and has greater impact than SVI on social life and function. Caregivers should be particularly aware of RVD, its consequences, and help patients to seek assessments, treatment, and rehabilitation.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.111
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.129
GPT teacher head0.493
Teacher spread0.363 · 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

Citations24
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCurrent Gerontology and Geriatrics ResearchSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207