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Record W2007593731 · doi:10.1002/jhbs.20135

The lost direction in binocular vision: The neglected signs posted by Wells, Towne, and Leconte

2005· article· en· W2007593731 on OpenAlexaff
Nicholas Wade, Hiroshi Ono, Alistair P. Mapp

Bibliographic record

VenueJournal of the History of the Behavioral Sciences · 2005
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyBinocular visionAestheticsSocial psychologyCommunicationOptometryComputer visionArtComputer scienceMedicine

Abstract

fetched live from OpenAlex

Studies of vision have informed theories first in philosophy and then in psychology. Over the centuries, an increasing number of phenomena have been enlisted to refute or reinforce particular theories. Nowhere has this been more evident than in binocular vision. How we see a single world with two eyes is one of the oldest and most consistently studied topics in vision research. It has been discussed at least since the time of Aristotle and it has been examined experimentally since the second century, when Ptolemy defined lines of visual correspondence for the two eyes. Prior to Wheatstone's invention of the stereoscope in the 1830s, binocular vision had been studied in terms of visual directions. The stereoscope established distance (or depth) as well as direction as dimensions of binocular vision. Subsequently, depth rather than direction has been the principal concern of students of vision, and texts in English devoted to analyses of direction rather than depth have been neglected. We examine the experiments on binocular visual direction conducted by Wells before Wheatstone, and by Towne and LeConte after him, and discuss the reasons for their neglect.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.060
GPT teacher head0.317
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

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

Citations15
Published2005
Admission routes1
Has abstractyes

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