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Record W1985686932 · doi:10.1167/10.13.22

Global motion processing: Invariance with mean luminance

2010· article· en· W1985686932 on OpenAlexaff
Robert F. Hess, Alexandre Zaharia

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsLuminancePhysicsSpatial frequencyOpticsContrast (vision)Stimulus (psychology)Motion perceptionPsychophysicsInvariant (physics)MathematicsMotion (physics)PsychologyNeuroscience

Abstract

fetched live from OpenAlex

We examine how global translational motion sensitivity varies with the mean luminance of the stimulus. Using DC-balanced, spatially narrowband micropatterns (radial Log Gabors) matched in terms of detectability (multiples above contrast threshold), we show that global translational motion sensitivity is invariant with the mean luminance. Contrast detection thresholds, however, show a characteristic spatial frequency dependence on mean luminance. Similar results were found for central and peripheral regions of the field and for a range of different micropattern velocities (2.1 deg/s to 84 deg/s). Thus, the sensitivity of global motion processing that occurs in extrastriate cortical areas, unlike the detectability of the stimuli themselves that occurs in lower visual areas, does not vary with mean luminance.

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 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 score0.159
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.334
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 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

Citations3
Published2010
Admission routes1
Has abstractyes

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