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Record W2730456968 · doi:10.1093/geroni/igx004.375

ENHANCING LIFE AND CARE OF OLDER ADULTS THROUGH PARTNERSHIPS IN RESEARCH, EDUCATION AND PRACTICE.

2017· article· en· W2730456968 on OpenAlexaffabout
M. Sharratt, Josie d’Avernas

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsResearch Institute for Aging
Fundersnot available
KeywordsPreparednessExcellenceFront lineWorkforceLong-term carePolitical scienceGerontologyNursingEconomic growthMedical educationPublic relationsMedicine

Abstract

fetched live from OpenAlex

The Schlegel-UW Research Institute for Aging (RIA), Waterloo, Canada, has a distributed network across Ontario of 16 continuum of care Villages housing over 3,000 residents. Emphasis is placed on learning, research, and innovation in long-term care and retirement through research-informed practice change and innovation in workforce preparedness. The newest Village is contiguous with a 30,000 sq.ft. research building (RIA) as part of a unique Centre of Excellence. The magic of this infrastructure is that it brings potential front-line workers in contact with university students, researchers, and labs, and provides an opportunity to mingle with the residents of the Village (Living Classroom). In response to the aging demographic and a resource-limited system, the RIA is a catalyst for the development and spread of innovation that enhances the quality of life and care for older adults.

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)0.019
metaresearch head score (Gemma)0.024
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: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0060.005
Open science0.0010.017
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.175
GPT teacher head0.503
Teacher spread0.328 · 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
GenreOther

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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