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Record W2329901534 · doi:10.1177/154193120304701307

Visual Momentum and Task Switching with 2D and 3D Displays of Geographic Terrain

2003· article· en· W2329901534 on OpenAlexaff
Justin G. Hollands, Nada Ivanovic, Yukari Enomoto

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2003
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsDefence Research and Development Canada
FundersVedecká Grantová Agentúra MŠVVaŠ SR a SAV
KeywordsTerrainTransition (genetics)Task (project management)Stereo displayMomentum (technical analysis)Computer scienceComputer graphics (images)GeographyEngineeringCartographyBusinessChemistry

Abstract

fetched live from OpenAlex

We were interested in determining if the visual momentum provided by gradual transition between two- and three-dimensional (2D and 3D) views of geographic terrain aided task switching. Twenty-two participants made judgments about the properties of two points placed on 2D or 3D displays of terrain. Participants performed the tasks in pairs of trials, switching tasks and displays between trials. On half the trials (continuous transition), the display dynamically rotated in depth from one display format to the other. On the other half (discrete transition), participants were immediately shown the alternate display format. The results showed that response time after transition was less for the continuous condition, and that accuracy was greater for the continuous condition, especially for the 3D display. We argue that this was because the continuous transition provided improved visual momentum between consecutive displays, and recommend the use of dynamic transition when switching views on geographic terrain.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.416

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 head0.006
GPT teacher head0.198
Teacher spread0.193 · 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 designObservational
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

Citations4
Published2003
Admission routes1
Has abstractyes

Explore more

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