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Record W2552465697 · doi:10.29085/9781783300730.018

Mobile wellness innovation: a Qi Gong app to improve wellness andcognitive resiliency in older adults

2018· book-chapter· en· W2552465697 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.

Bibliographic record

VenueFacet eBooks · 2018
Typebook-chapter
Languageen
FieldMedicine
TopicBiofield Effects and Biophysics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMoodQuality of life (healthcare)Mobile appsCognitionPsychologyGerontologyEmpowermentSittingMedicineClinical psychologyPsychotherapistComputer sciencePsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

This pilot project explored the utility of a mobile health and wellness app to older adults interested in using low-impact exercise as a protective factor against memory loss and mood swings. While it is known that exercise is a protective factor in preventing further cognitive regression, it is shown that adults aged 55 and older spend ten hours or more each day sitting or lying down, leaving them even more compromised (Cavill, Richardson and Foster, 2012). The piloting of a health and wellness self-management tool through a mobile app featuring the Chinese exercise of Qi Gong represents an innovative, visual and accessible tool that supports daily physical activity while fostering a sense of personal empowerment and enhancing the quality of life.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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