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Record W2725977465 · doi:10.1093/geroni/igx004.4768

ADDRESSING DEMENTIA IN NORTH AMERICA: CURRENT STATUS AND FUTURE DIRECTIONS

2017· article· en· W2725977465 on OpenAlexaboutno aff
Linda Garcia, Michelle Marie Gillis

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaPsychological interventionIntervention (counseling)GerontologyDiseaseMedicinePsychologyEconomic growthPolitical sciencePsychiatryEconomics

Abstract

fetched live from OpenAlex

Alzheimer’s Disease and related dementias constitute a major and growing challenge to the wellbeing of individuals, families and society in the United States and Canada. The prevalence of dementia in the US is projected to almost triple from 5 million persons now to 14 million by mid-century. In Canada, the number of persons affected will nearly double from about 750,000 to 1.4 million. Actions underway in Canada in research, caregiver support and community intervention will be presented. Using the US National Dementia Plan as a model, it will be argued that a comprehensive and multi-sectoral approach is necessary that includes: public awareness and community and workplace interventions; basic and applied research leading to better prevention, diagnosis, treatment and eventually, a cure; quality clinical care and support for affected individual and families.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0060.008
Open science0.0020.004
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0150.002

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 head0.058
GPT teacher head0.391
Teacher spread0.334 · 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 designNot applicable
Domainnot available
GenreReview

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 routes1
Has abstractyes

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