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Record W2134347861 · doi:10.3233/ves-2007-175-607

Effect of field of view on the Levitation Illusion

2008· article· en· W2134347861 on OpenAlexaff
H. L. Jenkin, James E. Zacher, Michael Jenkin, Charles M. Oman, Laurence R. Harris

Bibliographic record

VenueJournal of Vestibular Research · 2008
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsIllusionLevitationObserver (physics)Computer visionTilt (camera)Field of viewComputer scienceField (mathematics)PsychologyArtificial intelligenceOpticsPhysicsCognitive psychologyEngineeringMathematicsElectrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Supine subjects inside a furnished room in which both they and the room are pitched 90 degrees backwards may experience themselves and the room as upright relative to gravity. This effect is known as the levitation illusion because observers report that their arms feel weightless when extended, and objects hanging in the room seem to "levitate". This illusion is an extreme example of a visually induced illusion of static tilt. Visually induced tilt illusions are commonly experienced in wide-screen movie theatres, flight simulators, and immersive virtual reality systems. For technical reasons an observer's field of view is often constrained in these environments. No studies have documented the effect of field-of-view (FOV) restriction on the incidence of the levitation illusion. Preliminary findings suggest that when concurrently manipulating the FOV and observer position within an environment, the incidence of levitation illusions depends not only on the field of view but also on the visible scene content.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.227
GPT teacher head0.480
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2008
Admission routes1
Has abstractyes

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