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Record W2626241933

Support for sensory-cancellation effects during visual perception of congruent movements

2011· article· en· W2626241933 on OpenAlexaff
April D Karlinsky, Cynthia Lau, Paul Campagnero, Graeme Kirkpatrick, Romeo Chua, Nicola J. Hodges

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStimulus (psychology)PsychologyPerceptionSensory systemAudiologyCognitive psychologyCommunicationNeuroscienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

A sensory cancellation effect is presumed to result when participants move 'congruently' during a visual discrimination task. Indirect evidence for this has been shown (Miall et al., 2006), but in this study, only background stimuli were incongruent/ congruent, the target stimuli were always movement incongruent. Therefore, we manipulated target and stimulus-movement congruency during arm flexion/ extension movements. Congruent stimuli were directionally in-phase. Incongruent stimuli were directionally anti-phase, AP or random. Nine participants responded to a change in colour of hand images. Voice RTs were recorded from trials lasting ~200 s (~20 RTs). RTs were faster when the stimuli were sequential vs. random, when not moving. This effect was magnified during movement (Stim x Move, p = .01). Of interest was a Stimulus x Target Congruency interaction (p

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)0.002
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.039
GPT teacher head0.278
Teacher spread0.239 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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