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Record W2067303005 · doi:10.1037/a0017606

Grasping beer mugs: On the dynamics of alignment effects induced by handled objects.

2010· article· en· W2067303005 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 Experimental Psychology Human Perception & Performance · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaJames S. McDonnell Foundation
KeywordsGRASPCued speechObject (grammar)Task (project management)Coding (social sciences)Computer scienceArtificial intelligenceCommunicationPsychologyComputer visionCognitive psychologyMathematics

Abstract

fetched live from OpenAlex

We examined automatic spatial alignment effects evoked by handled objects. Using color as the relevant cue carried by an irrelevant handled object aligned or misaligned with the response hand, responses to color were faster when the handle aligned with the response hand. Alignment effects were observed only when the task was to make a reach and grasp response. No alignment effects occurred if the response involved a left-right key press. Alignment effects emerged over time, becoming more apparent either when the color cue was delayed or when relatively long, rather than short, response times were analyzed. These results are consistent with neurophysiological evidence indicating that the cued goal state has a modulatory influence on sensorimotor representations, and that handled objects initially generate competition between neural populations coding for a left- or right-handed action that must be resolved before a particular hand is favored.

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 score0.070
Threshold uncertainty score0.505

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 integrity0.0000.001
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 head0.031
GPT teacher head0.326
Teacher spread0.295 · 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