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Record W3113342935 · doi:10.1163/22134808-bja10043

Visual Self-Motion Feedback Affects the Sense of Self in Virtual Reality

2020· article· en· W3113342935 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

VenueMultisensory Research · 2020
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAvatarMotion (physics)PsychologyBody schemaVirtual realityImmersion (mathematics)Biological motionRepresentation (politics)CommunicationComputer visionArtificial intelligenceHuman–computer interactionComputer sciencePerceptionMathematics

Abstract

fetched live from OpenAlex

We assessed how self-motion affects the visual representation of the self. We constructed a novel virtual-reality experiment that systematically varied an avatar's motion and also biological sex. Participants were presented with pairs of avatars that visually represented the participant ('self-avatar'), or another person ('opposite avatar'). Avatar motion either corresponded with the participant's motion, or was decoupled from the participant's motion. The results show that participants identified with (i) 'self-avatars' over 'opposite-avatars', (ii) avatars moving congruently with self-motion over incongruent motion, and importantly (iii) with the 'opposite avatar' over the 'self-avatar' when the opposite avatar's motion was congruent with self-motion. Our results suggest that both self-motion and biological sex are relevant to the body schema and body image and that congruent bottom-up visual feedback of self-motion is particularly important for the sense of self and capable of overriding top-down self-identification factors such as biological sex.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.394
Teacher spread0.257 · 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