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Record W2033381433 · doi:10.1167/13.12.14

Allocentric visual cues influence mental transformation of bodies

2013· article· en· W2033381433 on OpenAlexafffund
Nora Preuss, Lara Harris, Fred W. Mast

Bibliographic record

VenueJournal of Vision · 2013
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungYork University
KeywordsPsychologyCognitive psychologyTransformation (genetics)Sensory cueBiology

Abstract

fetched live from OpenAlex

Identifying a human body stimulus involves mentally rotating an embodied spatial representation of one's body (motoric embodiment) and projecting it onto the stimulus (spatial embodiment). Interactions between these two processes (spatial and motoric embodiment) may thus reveal cues about the underlying reference frames. The allocentric visual reference frame, and hence the perceived orientation of the body relative to gravity, was modulated using the York Tumbling Room, a fully furnished cubic room with strong directional cues that can be rotated around a participant's roll axis. Sixteen participants were seated upright (relative to gravity) in the Tumbling Room and made judgments about body and hand stimuli that were presented in the frontal plane at orientations of 0°, 90°, 180° (upside down), or 270° relative to them. Body stimuli have an intrinsic visual polarity relative to the environment whereas hands do not. Simultaneously the room was oriented 0°, 90°, 180° (upside down), or 270° relative to gravity resulting in sixteen combinations of orientations. Body stimuli were more accurately identified when room and body stimuli were aligned. However, such congruency did not facilitate identifying hand stimuli. We conclude that static allocentric visual cues can affect embodiment and hence performance in an egocentric mental transformation task. Reaction times to identify either hands or bodies showed no dependence on room orientation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.154

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 communication0.0000.001
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 head0.258
Teacher spread0.252 · 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 designBench or experimental
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

Citations8
Published2013
Admission routes2
Has abstractyes

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