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Record W2161566213 · doi:10.1177/0956797610378307

A Functional Role for Motor Simulation in Identifying Tools

2010· article· en· W2161566213 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

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsWestern University
Fundersnot available
KeywordsEmbodied cognitionPsychologyCognitionNeuropsychologyIdentification (biology)Cognitive psychologyTask (project management)Orientation (vector space)Human–computer interactionCognitive scienceComputer scienceArtificial intelligenceNeuroscienceEngineering

Abstract

fetched live from OpenAlex

Embodied cognition promotes the involvement of the motor system in cognitive processing, such as tool identification. Although neuropsychological studies suggest that the motor system is not necessary for identifying tools, it may still have a functional role in tool recognition. To test this possibility, we used a motor interference task: Participants squeezed a rubber ball in one hand while naming pictures of tools and animals. Participants were faster and more accurate in naming the tools that were oriented with the handle facing away from the squeezing hand than in naming the tools that were oriented with the handle facing toward the squeezing hand. There was no effect of orientation for animals. Given that participants simulate grasping a tool with the hand closest to the handle, this result demonstrates that interfering with the ability to simulate grasping impairs tool naming and suggests that motor simulation has a functional role in tool identification.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.169
GPT teacher head0.442
Teacher spread0.273 · 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