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Record W2125232104 · doi:10.1037/a0023509

Priming of reach and grasp actions by handled objects.

2011· article· en· W2125232104 on OpenAlexafffund
Michael E. J. Masson, Daniel N. Bub, Andreas T. Breuer

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2011
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGRASPObject (grammar)Orientation (vector space)AffordancePriming (agriculture)Action (physics)Artificial intelligenceCommunicationComputer visionConstraint (computer-aided design)Computer scienceFunction (biology)MathematicsPsychologyHuman–computer interactionGeometryPhysics

Abstract

fetched live from OpenAlex

Pictures of handled objects such as a beer mug or frying pan are shown to prime speeded reach and grasp actions that are compatible with the object. To determine whether the evocation of motor affordances implied by this result is driven merely by the physical orientation of the object's handle as opposed to higher-level properties of the object, including its function, prime objects were presented either in an upright orientation or rotated 90° from upright. Rotated objects successfully primed hand actions that fit the object's new orientation (e.g., a frying pan rotated 90° so that its handle pointed downward primed a vertically oriented power grasp), but only when the required grasp was commensurate with the object's proper function. This constraint suggests that rotated objects evoke motor representations only when they afford the potential to be readily positioned for functional action.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.131
GPT teacher head0.392
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations80
Published2011
Admission routes2
Has abstractyes

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