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Record W2166169250 · doi:10.1258/jtt.2012.120605

An evaluation of preventive sensor technology for dementia care

2013· article· en· W2166169250 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

VenueJournal of Telemedicine and Telecare · 2013
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIntervention (counseling)DementiaFeelingNursingWarning systemMedicineAging in placeMedical emergencyPsychologyGerontologyComputer science

Abstract

fetched live from OpenAlex

We evaluated a commercially-available monitoring system for older people with dementia living at home. The system was designed to detect problems before they require crisis intervention. Fourteen clients from two healthcare organisations in the Netherlands used the system over a 9-month period. The formal and informal caregivers were interviewed, project group meetings were observed, nurse diaries were analysed and a cost analysis performed. Clients and informal caregivers reported enhanced feelings of safety and security as a result of having the system installed in the home. The system appeared to reduce the burden of care on the informal caregiver and had the potential to allow people to live at home for longer. There were financial savings for clients staying at home with the technology compared with the costs of staying in a nursing home: for 10 clients living at home for 2 months, the savings were 23,665 euro. The study showed that the monitoring system represents a potentially useful early warning system to detect a situation before it requires emergency intervention.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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