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Record W2586340927

Crossed Hands Curve Saccades: Multisensory Dynamics in Saccade Trajectories

2008· article· en· W2586340927 on OpenAlexfundno aff
Lauren L. Emberson, Rebecca J. Weiss, Adriano Vilela Barbosa, Eric Vatikiotis‐Bateson

Bibliographic record

VenueeScholarship (California Digital Library) · 2008
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsSaccadeAction (physics)PerceptionPsychologyCognitive scienceCognitive psychologyEye movementPhysicsNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

Crossing one's hands across the midline can interfere with multisensory processing.The current experiment examines this effect in a dynamic framework.Participants were asked to saccade to visual targets in the presence of a manual tactile distraction on the same or opposite side of the target and with hands crossed or uncrossed.Trajectories of the resulting visual saccades were analyzed for curvature.While spatially incongruent trials in an uncrossed position resulted in marginal saccade curvature, the crossed hand condition caused significant curvature when compared to control trials regardless of spatial configuration.Thus, the current study provides evidence that the role of sensory integration in eye movement dynamics is modulated by relative positioning of the hands.Moreover, the findings indicate that saccades can deviate in the presence of crossed-hand stimulation regardless of the spatial configuration of the trial.These results provide an initial link between known multisensory phenomena and saccade trajectories.

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)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.282
Teacher spread0.244 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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