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Record W2017038174 · doi:10.1080/00222890009601385

Monocular and Binocular Vision in the Control of Goal-Directed Movement

2000· article· en· W2017038174 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Motor Behavior · 2000
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsSimon Fraser UniversityUniversity of WindsorMcMaster University
Fundersnot available
KeywordsMonocularBinocular visionMovement (music)Monocular visionPsychologyVisual feedbackComputer visionControl (management)Artificial intelligenceCommunicationCognitive psychologyComputer sciencePhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

In the present research the authors examined the time course of binocular integration in goal-directed aiming and grasping. With liquid-crystal goggles, the authors manipulated vision independently to the right and left eyes of 10 students during movement preparation and movement execution. Contrary to earlier findings reported in catching experiments (I. Olivier, D. J. Weeks, K. L. Ricker, J. Lyons, & D. Elliott, 1998), neither a temporal nor a spatial binocular advantage was obtained in 1 grasping and 2 aiming studies. That result suggests that, at least in some circumstances, monocular vision is sufficient for the precise control of limb movements. In a final aiming experiment involving 3-dimensional spatial variability and no trial-to-trial visual feedback about performance, binocular vision was associated with greater spatial accuracy. Binocular superiority appeared to be most pronounced when participants were unable to adjust their limb control strategy or procedure on the basis of terminal feedback about performance.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.232

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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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