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Record W2162017466 · doi:10.1177/0956797612463402

Reduced Temporal Fusion in Near-Hand Space

2013· article· en· W2162017466 on OpenAlexafffund
Stephanie C. Goodhew, Davood G. Gozli, Susanne Ferber, Jay Pratt

Bibliographic record

VenuePsychological Science · 2013
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMasking (illustration)Backward maskingVisibilityPsychologyVisual maskingComputer visionObject (grammar)Visual processingArtificial intelligenceVisual perceptionCommunicationVisual spaceIndividuationCognitive psychologyComputer sciencePerceptionNeurosciencePhysicsOptics

Abstract

fetched live from OpenAlex

Object-substitution masking (OSM) is thought to reflect a failure of object individuation. That is, a briefly presented target surrounded by four dots is perceptually fused with the four-dot mask when the mask is visible after the target has disappeared, thereby obscuring the visibility of the target. If OSM depends on the inability to temporally segregate objects, then increasing the temporal precision of the visual system should reduce OSM. In the study reported here, we manipulated temporal precision by varying the proximity of participants' hands to visual stimuli, because stimuli in near-hand space have been found to enjoy enhanced attentional processing, and attention is known to speed visual processing. Hand placement was indeed found to affect OSM: Placing participants' hands near the visual stimuli reduced the magnitude of the masking. This finding demonstrates that object individuation can be facilitated by increasing the temporal resolution of vision via increasing the proximity of visual stimuli to the hands.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.459
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.113
GPT teacher head0.405
Teacher spread0.292 · 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; both teacher heads agree on what is shown here.

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

Citations46
Published2013
Admission routes2
Has abstractyes

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