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Record W2018337957 · doi:10.1145/968363.968384

ECSGlasses and EyePliances

2004· article· en· W2018337957 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceHuman–computer interactionWearable computerEye contactModality (human–computer interaction)PhoneProcess (computing)Encoding (memory)Wearable technologyArtificial intelligenceCommunicationPsychologyEmbedded system

Abstract

fetched live from OpenAlex

We present ECSGlasses: wearable eye contact sensing glasses that detect human eye contact. ECSGlasses report eye contact to digital devices, appliances and EyePliances in the user's attention space. Devices use this attentional cue to engage in a more sociable process of turn taking with users. This has the potential to reduce inappropriate intrusions, and limit their disruptiveness. We describe new prototype systems, including the Attentive Messaging Service (AMS), the Attentive Hit Counter, the first person attentive camcorder eyeBlog, and an updated Attentive Cell Phone. We also discuss the potential of these devices to open new windows of interaction using attention as a communication modality. Further, we present a novel signal-encoding scheme to uniquely identify EyePliances and users wearing ECSGlasses in multiparty scenarios.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.116

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 head0.009
GPT teacher head0.229
Teacher spread0.219 · 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

Quick stats

Citations35
Published2004
Admission routes1
Has abstractyes

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