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Record W2002878039 · doi:10.1145/2702613.2702631

Smart for Life

2015· article· en· W2002878039 on OpenAlexaff
Sarah Mennicken, Amy Hwang, Rayoung Yang, Jesse Hoey, Alex Mihailidis, Elaine M. Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsComputer scienceHome automationWork (physics)Emerging technologiesKnowledge managementData scienceHuman–computer interactionEngineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

As sensing and actuation technologies grow more widespread, smart home infrastructures will become both feasible and flexible in supporting multiple applications. The development of these "smart home technologies" have been investigated by diverse fields spanning technical, sociological, and health-oriented disciplines, attempting to meet varying users' needs from technology savvy, "mass market", and functionally declining older adult populations. In an effort to promote human-centred knowledge exchange and design expertise between these communities, this workshop aims to explore interaction design for intended smart home users at and transitioning between successive life stages. Ultimately, we will aim to address how smart home technologies can be designed to evolve with their users over the life course. By uniting researchers and designers from various backgrounds, we hope to stimulate both actionable insights and design artifacts that better capture the evolutionary nature of users and their home contexts, which participants can then apply in their own research and design work going forward.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.288

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 science0.0000.000
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 head0.094
GPT teacher head0.320
Teacher spread0.225 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2015
Admission routes1
Has abstractyes

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