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Record W3004454982 · doi:10.2196/17514

Dementia-Related Products on an e-Commerce Platform

2020· article· en· W3004454982 on OpenAlexvenueno aff
Benjamin K.P. Woo

Bibliographic record

VenueJMIR Biomedical Engineering · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaProduct (mathematics)NeurocognitiveInternet privacyPsychologyBusinessMedicinePsychiatryComputer scienceCognitionDisease

Abstract

fetched live from OpenAlex

Dementia is a neurocognitive disorder, which affects older adults. There are currently no medication treatments available to cure dementia, but a number of biomedical technologies could be useful in assisting patients with dementia. With the continued growth of electronic commerce (e-commerce), online shopping for aging and health-related products will only continue to increase. Using the Tmall marketplace as an example, the purpose of this viewpoint is to describe the current trends of dementia-related products and devices available on an e-commerce platform. Feedback and critiques in the form of consumer reviews should be used to improve the design of dementia-related products. Online medical product consumers, however, must be vigilant about the effectiveness and risks of these biomedical devices.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0440.034

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 head0.047
GPT teacher head0.384
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2020
Admission routes1
Has abstractyes

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