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Record W1993149955 · doi:10.1080/00222890903566343

Determining the Temporal Limits of a Visual Sample for Visual Regulation

2010· article· en· W1993149955 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 · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDuration (music)Context (archaeology)Sample (material)Movement (music)PsychologyVisual perceptionAudiologyCommunicationCognitive psychologyPerceptionNeuroscienceMedicineGeographyChemistry

Abstract

fetched live from OpenAlex

The author examined the minimum amount of time needed for vision to increase aiming accuracy and decrease movement duration. Participants selected when they would receive a visual sample during aiming movements by pressing a switch held with the left hand. The sample was one of the following durations: 40 ms, 30 ms, 20 ms, 10 ms, or 0 ms (no vision). Decreased accuracy in the no-vision condition compared to the vision conditions was observed when the duration of the impending sample was unknown (Experiment 1). Samples 40 ms in duration were sufficient to decrease endpoint variability when the duration of the sample was known before the movement (Experiment 2). These results indicate that short visual samples can be used to decrease movement time and increase accuracy and that knowledge of the impending visual context can impact the individual's subsequent behavior.

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)0.001
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 score0.786
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.342
Teacher spread0.284 · 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