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Record W7079098776 · doi:10.17632/bccfxy9t37

Learning improves the contribution of auditory distance cues to size constancy in perception and grasping when vision is limited

2025· dataset· en· W7079098776 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

VenueMendeley Data · 2025
Typedataset
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsWestern University
Fundersnot available
KeywordsSubjective constancyPerceptionProprioceptionTask (project management)Object (grammar)Contrast (vision)Multisensory integrationAction (physics)Perceptual system

Abstract

fetched live from OpenAlex

When vision is restricted, proprioceptive distance cues fully restore size constancy for scaling grip aperture when grasping objects, despite only limited improvement in perceptual judgments of object size. This suggests that specific task demands and associated neural mechanisms determine the relative weighting of cues during multisensory integration. Is this specific to proprioceptive cues? Here, we examined the contribution of auditory information to perception and action systems under restricted viewing conditions. Surprisingly, in contrast to proprioception, providing auditory distance information had no impact whatsoever on size constancy in grasping but did improve perceptual judgments of size. After participants received extensive training in discriminating distance from auditory cues, there was a modest improvement in grip scaling. Taken together, we suggest that the neural mechanisms mediating grasping cannot incorporate distance information from audition as easily as they can from proprioception when computing real-world object size but this ability can be improved with training.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.059
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0020.002
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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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