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Record W2896098622 · doi:10.1145/3267782.3267798

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2018· article· en· W2896098622 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaNvidia
KeywordsComputer visionOptical head-mounted displayComputer scienceArtificial intelligenceEye trackingVirtual realityHead (geology)TerrainTracking (education)Eye movementSimulationComputer graphics (images)GeographyPsychology

Abstract

fetched live from OpenAlex

We present two experiments evaluating the effectiveness of the eye as a controller for travel in virtual reality (VR). We used the FOVE head-mounted display (HMD), which includes an eye tracker. The first experiment compared seven different travel techniques to control movement direction while flying through target rings. The second experiment involved travel on a terrain: moving to waypoints while avoiding obstacles with three travel techniques. Results of the first experiment indicate that performance of the eye tracker with head-tracking was close to head motion alone, and better than eye-tracking alone. The second experiment revealed that completion times of all three techniques were very close. Overall, eye-based travel suffered from calibration issues and yielded much higher cybersickness than head-based approaches.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.995

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)0.0000.006

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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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

Citations19
Published2018
Admission routes2
Has abstractyes

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