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Record W2063581581 · doi:10.3389/fnhum.2012.00332

Grasping time does not influence the early adherence of aperture shaping to Weber's law

2012· article· en· W2063581581 on OpenAlexafffund
Matthew Heath, Scott A. Holmes, Ali Mulla, Gordon Binsted

Bibliographic record

VenueFrontiers in Human Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British ColumbiaInterior HealthWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHumCognitionPsychologyNeuroscienceFront (military)Cognitive scienceLawHistoryPolitical sciencePhysicsArt history

Abstract

fetched live from OpenAlex

The "just noticeable difference" (JND) represents the minimum amount by which a stimulus must change to produce a noticeable variation in one's perceptual experience (i.e., Weber's law). Recent work has shown that within-participant standard deviations of grip aperture (i.e., JNDs) increase linearly with increasing object size during the early, but not the late, stages of goal-directed grasping. A visually based explanation for this finding is that the early and late stages of grasping are respectively mediated by relative and absolute visual information and therefore render a time-dependent adherence to Weber's law. Alternatively, a motor-based explanation contends that the larger aperture shaping impulses required for larger objects gives rise to a stochastic increase in the variability of motor output (i.e., impulse-variability hypothesis). To test the second explanation, we had participants grasp differently sized objects in grasping time criteria of 400 and 800 ms. Thus, the 400 ms condition required larger aperture shaping impulses than the 800 ms condition. In line with previous work, JNDs during early aperture shaping (i.e., at the time of peak aperture acceleration and peak aperture velocity) for both the 400 and 800 ms conditions scaled linearly with object size, whereas JNDs later in the response (i.e., at the time of peak grip aperture) did not. Moreover, the 400 and 800 ms conditions produced comparable slopes relating JNDs to object size. In other words, larger aperture shaping impulses did not give rise to a stochastic increase in aperture variability at each object size. As such, the theoretical tenets of the impulse-variability hypothesis do not provide a viable framework for the time-dependent scaling of JNDs to object size. Instead, we propose that a dynamic interplay between relative and absolute visual information gives rise to grasp trajectories that exhibit an early adherence and late violation to Weber's law.

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)0.001
metaresearch head score (Gemma)0.026
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 score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.035
GPT teacher head0.264
Teacher spread0.229 · 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

Citations33
Published2012
Admission routes2
Has abstractyes

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