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Record W2064773722 · doi:10.1167/7.9.273

Adaptation to circular patterns influences the perception of distorted squares

2010· article· en· W2064773722 on OpenAlexaff
Isabelle Legault, Rémy Allard, J. Faubert

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsStimulus (psychology)Adaptation (eye)PerceptionAmplitudeMathematicsPsychologyCommunicationCognitive psychologyNeurosciencePhysicsOptics

Abstract

fetched live from OpenAlex

It as been argued that an adaptation paradigm can be used to establish links between neural activity and perception. The purpose of the present study was to determine if three adaptation patterns influence the shape perception of distorted squares. The adaptation stimuli were circular and contained radial (circular), angular, or plaid (2 sine waves) spatial frequencies. The target stimuli were squares with contours varying in amplitude. The adaptation stimulus was presented for 5 seconds followed by the target for 500ms. Thresholds were obtained with a forced choice paradigm where the subject had to indicate whether the stimulus was curved inward or outward. Results show that the adaptation patterns influenced the responses in different ways. Radial adaptation patterns caused a significant threshold increase while the other adaptation patterns had no influence. This suggests that mechanisms involved in processing circular patterns share common neural pathways with those that process distorted squares.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.350
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2010
Admission routes1
Has abstractyes

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