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Record W2998983552 · doi:10.29173/hsi160

Dementia in Canadian primary health care: The potential role of case management

2019· article· en· W2998983552 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Science Inquiry · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsDementiaPrimary careMedicinePrimary health careNursingGerontologyFamily medicineEnvironmental healthPathologyDisease

Abstract

fetched live from OpenAlex

Dementia is a chronic disease characterized by progressive memory loss and behavioural disturbance. It has become a major concern for healthcare professionals due to the increasing number of people affected, usually presenting with more than one chronic condition. 1 According to the World Health Organization (WHO), up to eight million new cases of dementia are detected world-wide annually. 2 Today in Canada, half a million people are living with dementia and this number is expected to rise two and a half times over the next 40 years due to an aging population. The WHO has declared dementia to be one of the most serious health challenges facing our society due to its pronounced consequences on patients, their families and society. 2 Various elements contribute to this quandary including patient-caregiver dyad factors (e.g., fear of stigmatization) and healthcare system issues (e.g., fragmentation of healthcare services). In this article we discuss Case Management (CM) designed for patients with dementia, and types of CM pertinent to primary care.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.356
Teacher spread0.337 · 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