MétaCan
Menu
Back to cohort
Record W2071073238 · doi:10.1167/8.4.22

Amblyopic perception of biological motion

2008· article· en· W2071073238 on OpenAlexafffund
Benjamin Thompson, Nikolaus F. Troje, Bruce C. Hansen, Robert F. Hess

Bibliographic record

VenueJournal of Vision · 2008
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsQueen's UniversityMcGill University
FundersCanadian Institutes of Health Research
KeywordsBiological motionMotion (physics)PerceptionMasking (illustration)Motion perceptionComputer sciencePoint (geometry)Computer visionVisual perceptionVisual processingVisual maskingSIGNAL (programming language)Artificial intelligenceCommunicationPsychologyNeuroscienceMathematics

Abstract

fetched live from OpenAlex

Although a number of low-level visual deficits in amblyopia have been identified, it is still unclear to what extent these deficits extend throughout the visual processing hierarchy. Biological motion perception can be a useful measure of local and global visual processing since the point-light stimuli that are often used to study this ability carry both local motion and global form information. To investigate the integrity of the biological motion processing system in amblyopia, we employed both detection and discrimination tasks with coherent or scrambled point-light walkers either alone or embedded in different types of point-light masks. These manipulations allowed for control over the amount of form and/or motion information available to the observers that could be used for task performance. We found that amblyopic eyes could process both the global form and local motion components of point-light walkers, indicating intact processing for these stimuli. However, amblyopic eyes did show an increased susceptibility to the addition of masking dots suggesting that segregation of signal from noise is deficient in amblyopia.

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 score0.413
Threshold uncertainty score0.357

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 communication0.0000.000
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 head0.120
GPT teacher head0.370
Teacher spread0.250 · 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

Citations21
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of VisionSame topicVisual perception and processing mechanismsFrench-language works237,207