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Record W4294891745 · doi:10.1145/3550315

One Ring to Rule Them All

2022· article· en· W4294891745 on OpenAlexaff
Sandra Bardot, Bradley Rey, Lucas Audette, Kevin Fan, Da-Yuan Huang, Jun Li, Wei Li, Pourang Irani

Bibliographic record

VenueProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · 2022
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsHuawei Technologies (Canada)University of ManitobaUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsPopularityFocus (optics)Computer scienceHuman–computer interactionControl (management)Work (physics)Grounded theoryData scienceKnowledge managementPsychologyQualitative researchArtificial intelligenceSocial psychologyEngineeringSociology

Abstract

fetched live from OpenAlex

Smartrings have potential to extend our ubiquitous control through their always available and finger-worn location, as well as their quick and subtle interactions. As such, smartrings have gained popularity in research and in commercial usage; however, they often concentrate on a singular or novel aspect of a smartring's potential. While with any emerging technology the focus on these individual components is important, there is a lack of broader empirical understanding regarding a user's intentions for smartring usage. Thus in this work, we investigate concrete and reported smartring usage scenarios throughout the daily lives of participants. During a two-week in-situ diary study (N = 14), utilizing a mock smartring, we provide an initial understanding of the potential tasks, daily activities, connected devices, and interactions for which augmentation with a smartring was desired. We further highlight patterns of imagined smartring use found by our participants. Finally, we provide and discuss guidelines, grounded through our found knowledge, to inform research and development towards the design of future smartrings.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.231
Teacher spread0.216 · 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 designBench or experimental
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

Citations12
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesSame topicGreen IT and SustainabilityFrench-language works237,207