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Record W2006733343 · doi:10.1163/22134808-000s0091

The contribution of sound in determining the perceptual upright

2013· article· en· W2006733343 on OpenAlexaff
Michael J. Carnevale, Laurence R. Harris

Bibliographic record

VenueMultisensory Research · 2013
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsPerceptionPsychologyCharacter (mathematics)CommunicationSound (geography)LoudspeakerMonauralAcousticsMathematicsPhysics

Abstract

fetched live from OpenAlex

The perceived direction of up depends on visual, gravity, and body cues, each of which is given a weighting by the brain (Dyde et al., 2006). Little work has been done, however, to demonstrate whether sound might also be usable by the brain as a cue to up. Here we assess the possible contribution of sound to perceived orientation by adding a sound cue to gravity. The perceptual upright, the direction in which a character is most easily recognized, was assessed using the Oriented Character Recognition Test (OCHART). Subjects identified the character ‘p’ that was presented in various orientations (0–360 degrees rotation) as either a ‘p’ or ‘d’. The orientations were chosen by a QUEST adaptive staircase procedure and the mean of the points of subjective equality was taken as the perceptual upright. Subjects lay on their side and viewed a laptop screen through a shroud. Thus, body and gravity cues were orthogonal and swings of the perceptual upright towards or away from gravity could be measured. Loudspeakers were mounted above and below the lying subject (opposite the left and right ears) and sounds were presented synchronized to the appearance of the character on the screen. Changes in the direction of the PU were recorded depending on whether a sound was present or not. We conclude that sounds can contribute to the perception of upright.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.456
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.253
GPT teacher head0.439
Teacher spread0.186 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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