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Record W2762185336 · doi:10.1145/3131277.3132182

The eyes don't have it

2017· article· en· W2762185336 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 institutionsCarleton University
Fundersnot available
KeywordsSelection (genetic algorithm)Eye trackingComputer scienceHead (geology)GazeArtificial intelligenceTask (project management)Computer visionOptical head-mounted displayReciprocalVirtual realityEngineering

Abstract

fetched live from OpenAlex

We present a study comparing selection performance between three eye/head interaction techniques using the recently released FOVE head-mounted display (HMD). The FOVE offers an integrated eye tracker, which we use as an alternative to potentially fatiguing and uncomfortable head-based selection used with other commercial devices. Our experiment was modelled after the ISO 9241-9 reciprocal selection task, with targets presented at varying depths in a custom virtual environment. We compared eye-based selection, and head-based selection (i.e., gaze direction) in isolation, and a third condition which used both eye-tracking and head-tracking at once. Results indicate that eye-only selection offered the worst performance in terms of error rate, selection times, and throughput. Head-only selection offered significantly better performance.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.683

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.028
GPT teacher head0.296
Teacher spread0.268 · 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

Citations164
Published2017
Admission routes1
Has abstractyes

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