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Record W2730471759 · doi:10.1093/geroni/igx004.2524

THE HEALTHY STAY VOLUNTEERS AS PARTNERS IN SENIOR-FRIENDLY CARE

2017· article· en· W2730471759 on OpenAlexaff
J.E. Denomme, Daniel L. Brown, B. O’Leary, J. Lee, Brittany Singleton

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsDeliriumVolunteerMedicineNursingAcute carePsychologyHealth carePsychiatry

Abstract

fetched live from OpenAlex

The goal of the Healthy Stay Volunteer Program is to help patients keep a healthy mind and stay physically active during a hospital stay. Since the fall of 2015, over 150 volunteers have been trained to support our strategy to prevent delirium and promote mobilization. Volunteers serve 11 acute care units encouraging patients to ambulate and/or perform simple exercises depending on their level of mobility. They provide friendly visiting, promote orientation, assist with practical matters like using the telephone, and provide cognitive stimulation. The program provides the volunteer with an interactive experience to work with an elderly population in an acute care setting with the support of a dedicated interprofessional team. The Healthy Stay Volunteer program has flourished and supports the sustainability of process change implemented through our corporate senior friendly strategy.

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)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0050.003
Open science0.0020.015
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.002

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 head0.041
GPT teacher head0.404
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 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 routes1
Has abstractyes

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