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Record W7029180095

The Impact of Perceptual Organization on the Limits of Binocular Fusion

2021· other· en· W7029180095 on OpenAlexaff

Bibliographic record

VenueYork University Digital Library (York University) · 2021
Typeother
Languageen
FieldSocial Sciences
TopicGerman Social Sciences and History
Canadian institutionsYork University
Fundersnot available
KeywordsMonocularPerceptionBinocular disparityProcess (computing)Object (grammar)Binocular visionStereopsisVisual perceptionReceptive field
DOInot available

Abstract

fetched live from OpenAlex

As a consequence of the separation of the two eyes in the head, the images of objects projected onto the two retinas are in different positions, called binocular disparity. The brain uses this positional information to represent the 3D layout or depth in a scene, a process called stereopsis. The two monocular half-images of objects will be integrated and seen as single if the binocular disparity is within Panums fusional area. Objects with disparities beyond this region will be seen as double. There are likely many factors which influence the perception of diplopia, including cognition (i.e., attention or suppression) or low-level object features (i.e., size). This thesis evaluates the proposal that higher-order visual processing, grouping through uniform connectedness, diminishes the perception of diplopia. To this end, in a series of experiments I presented isolated single elements, pairs of isolated and connected elements, and elements with varying levels of connectedness. Taken together, the results show that connecting elements elevates diplopia thresholds. This result is consistent with both the impact of perceptual organization and the use of larger receptive fields to process the disparity of the object. These two possibilities are discussed along with future experiments designed to distinguish between these accounts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.216
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.202
Teacher spread0.184 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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