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Record W2109594083 · doi:10.1080/13554794.2014.922994

A blind human expert echolocator shows size constancy for objects perceived by echoes

2014· article· en· W2109594083 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNeurocase · 2014
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsOntario Brain InstituteWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHuman echolocationSubjective constancyContrast (vision)Computer visionCommunicationComputer scienceArtificial intelligenceSightPsychologyColor constancyCognitive psychologyPerceptionPhysicsOpticsNeuroscienceImage (mathematics)

Abstract

fetched live from OpenAlex

Some blind humans make clicking noises with their mouth and use the reflected echoes to perceive objects and surfaces. This technique can operate as a crude substitute for vision, allowing human echolocators to perceive silent, distal objects. Here, we tested if echolocation would, like vision, show size constancy. To investigate this, we asked a blind expert echolocator (EE) to echolocate objects of different physical sizes presented at different distances. The EE consistently identified the true physical size of the objects independent of distance. In contrast, blind and blindfolded sighted controls did not show size constancy, even when encouraged to use mouth clicks, claps, or other signals. These findings suggest that size constancy is not a purely visual phenomenon, but that it can operate via an auditory-based substitute for vision, such as human echolocation.

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)0.000
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 score0.125
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 science0.0000.000
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 head0.048
GPT teacher head0.326
Teacher spread0.278 · 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