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Record W2006209560 · doi:10.1007/s11136-013-0458-x

Innovations in e-health

2013· article· en· W2006209560 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

VenueQuality of Life Research · 2013
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsMcGill University Health Centre
FundersBiogenAstraZenecaRobert Wood Johnson Foundation
KeywordsQuality of Life ResearchPublic healthEnvironmental healthMedicineNursing

Abstract

fetched live from OpenAlex

The theme of ISOQOL's 19th Annual Conference in Budapest, Hungary, was The Journey of Quality of Life Research: A Path Towards Personalized Medicine. Innovations in e-health was one of four plenary panels. E-health is changing the landscape of clinical practice and health care, but the best way to leverage the many promised benefits of emerging e-health technologies is still not clear. The Innovations in e-health panel presented emerging changes in technologies and applications that will facilitate clinical decision making, improve quality and efficiency of care, engage individuals in clinical decision making, and empower them to adopt healthy behaviors. The purpose of this paper was to present emerging trends in e-health and considerations for successful adoption of new technologies, and an overview of each of the presentations in the e-health plenary. The presentations included a personal perspective on the use of technology for self-monitoring in Parkinson's disease, an overview of online social networks and emerging technologies, and the collection of patient-reported outcomes through web-based systems in clinical practice. The common thread across all the talks was the application of e-health tools to empower individuals with chronic disease to be actively engaged in the management of their health. Considerations regarding data ownership and privacy, universal access to e-health, interactivity between different types of e-health technologies, and tailoring applications to individual needs were explored.

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)0.019
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.582
GPT teacher head0.657
Teacher spread0.075 · 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