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Record W4415099611 · doi:10.1016/j.inpsyc.2025.100154

Acceptability and feasibility of a sensor-instrumented ‘SmartSocks’ wearable prototype to detect agitation in people with dementia

2025· article· en· W4415099611 on OpenAlexaff
Ikran Dahir, R. A. M. Ali, Neha Ghosalkar, Zahinoor Ismail, Antonieta Medina‐Lara, Joanne McDermid, Zeke Steer, P Venkatesh, Byron Creese

Bibliographic record

VenueInternational Psychogeriatrics · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Calgary
FundersKing's College LondonDepartment of Health and Social CareInnovate UKNational Institute for Health and Care Research
KeywordsDementiaWearable computerData sharingCode (set theory)Wearable technologyInformed consentData collectionData access

Abstract

fetched live from OpenAlex

Data availability: Code used in the data preparation and analysis is available at https://github.com/creesebyron/SmartSocks. Consent was not obtained for open posting of data. Data are embargoed on Brunel University of London’s research data repository, Figshare (10.17633/rd.brunel.30127036) and accessible via request. Access will be granted once users have consented to the data sharing agreement.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.348
Teacher spread0.333 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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