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Record W4402429811 · doi:10.1177/10711813241264199

Promoting Physical Activity With Augmented Reality Experiences

2024· article· en· W4402429811 on OpenAlexafffund
Mark Chignell, Debbie Barton, Lisa Fannin, Justine Estey, Danica Maillet, Caroline Lovens, Jalila Jbilou

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2024
Typearticle
Languageen
FieldComputer Science
TopicAI in Service Interactions
Canadian institutionsUniversité de MonctonCentre for Excellence in Mining InnovationUniversity of Toronto
FundersEnvironmental Trust Fund, Government of New Brunswick
KeywordsAugmented realityPsychologyHuman–computer interactionComputer science

Abstract

fetched live from OpenAlex

Between June 2021 and March 2023, the Centre for Innovation and Research in Aging (CIRA) evaluated the effectiveness of the 2RaceWithMe exergaming product from Centivizer Inc in two New Brunswick long term care homes. 2RaceWithMe provides physical activity, through seated exercise, for older adults. In 2RaceWithMe, exercise is motivated by the requirement that residents needs to keep pedaling in order to view scenic videos from around the world. The objective of this paper is to report on some of the qualitative results obtained in the CIRA study, and to assess some of the barriers and facilitators to the use of an exergaming product like 2RaceWithMe in long term 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.

How this classification was reachedexpand

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2024
Admission routes2
Has abstractyes

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