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Record W2031409562 · doi:10.1080/00222895.2015.1012579

Online Vision as a Function of Real-Time Limb Velocity: Another Case for Optimal Windows

2015· article· en· W2031409562 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Motor Behavior · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsNipissing UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWindow (computing)TrajectoryComputer visionConsistency (knowledge bases)Computer scienceControl (management)Physical medicine and rehabilitationPsychologyArtificial intelligenceSimulationMedicine

Abstract

fetched live from OpenAlex

The efficiency of online visuomotor processes was investigated by manipulating vision based on real-time upper limb velocity. Participants completed rapid reaches under two control (full vision, no vision) and three experimental visual window conditions. The experimental visual windows were early: 0.8-1.4 m/s, middle: above 1.4 m/s, and late: 1.4 to 0.8 m/s. The results indicated that endpoint consistency comparable to that of full-vision trials was observed when using vision from the early (43 ms) and middle (89 ms) windows, but vision from the middle window entailed a longer deceleration phase (i.e., a temporal cost). The late window was not useful to implement online trajectory amendments. This study provides further support for the idea of early visuomotor control, which may involve multiple online control processes during voluntary movement.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.401

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 head0.058
GPT teacher head0.317
Teacher spread0.259 · 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