MétaCan
Menu
Back to cohort
Record W2025991255 · doi:10.1068/p6130

Binocular Vision: Defining the Historical Directions

2009· article· en· W2025991255 on OpenAlexaff
Hiroshi Ono, Nicholas Wade, Linda Lillakas

Bibliographic record

VenuePerception · 2009
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsYork University
Fundersnot available
KeywordsPtolemy's table of chordsBrewsterEleventhKeplerObject (grammar)HistoryBinocular visionPhilosophyEpistemologyOpticsComputer scienceArtificial intelligencePhysicsComputer visionClassicsStars

Abstract

fetched live from OpenAlex

Ever since Kepler described the image-forming properties of the eye (400 years ago) there has been a widespread belief, which remains to this day, that an object seen with one eye is always seen where it is. Predictions made by Ptolemy in the first century, Alhazen in the eleventh, and Wells in the eighteenth, and supported by Towne, Hering, and LeConte in the nineteenth century, however, are contrary to this claimed veridicality. We discuss how among eighteenth- and nineteenth-century British researchers, particularly Porterfield, Brewster, and Wheatstone, the erroneous idea continued and also why observations made by Wells were neither understood nor appreciated. Finally, we discuss recent data, obtained with a new method, that further support Wells's predictions and which show that a distinction between headcentric and relative direction tasks is needed to appreciate the predictions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.020
Scholarly communication0.0040.008
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.310
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuePerceptionSame topicCategorization, perception, and languageFrench-language works237,207