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Record W2046083941 · doi:10.1080/00222895.2010.510544

Sequential Aiming with Two Limbs and the One-Target Advantage

2010· article· en· W2046083941 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 · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsWestern University
Fundersnot available
KeywordsMovement (music)Visual feedbackCommunicationPsychologyComputer scienceHand preferenceSequence (biology)Physical medicine and rehabilitationNeuroscienceCognitive psychologyArtificial intelligenceBiologyLateralityMedicine

Abstract

fetched live from OpenAlex

Movement times to the first target in a 2-target sequence are typically slower than in 1-target aiming tasks. The 1-target movement time advantage has been shown to emerge regardless of hand preference, the hand used, the amount of practice, and the availability of visual feedback. The authors tested central and peripheral explanations of the 1-target advantage, as postulated by the movement integration hypothesis, by asking participants to perform single-target movements, 2-target movements with 1 limb, and 2-target movements in which they switched limbs at the first target. Reaction time and movement time data showed a 1-target advantage that was similar for both 1- and 2-limb sequential aiming movements. This outcome demonstrates that the processes underlying the increase in movement time to the 1st target in 2-target sequences are not specific to the limb, suggesting that the 1-target advantage originates at a central rather than a peripheral level.

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 score0.407
Threshold uncertainty score0.219

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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