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Record W2136182195 · doi:10.1109/whc.2009.4810867

Evidence for haptic memory

2009· article· en· W2136182195 on OpenAlexafffund
Ron Shih, Adam Dubrowski, Heather Carnahan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of TorontoUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLift (data mining)Haptic technologyComputer scienceTorqueSimulationPsychologyPhysics

Abstract

fetched live from OpenAlex

The purpose of these experiments was to investigate the minimum duration of haptic memory representations. The term haptic memory can be defined as the ability to retain impressions of haptically acquired information after the original stimulus is absent. Participants repeatedly picked up objects of various masses. The time interval between the final practice lift of each object and a test lift was manipulated. In the 0 second delay condition, there was no delay between the release of the object after the final practice lift and the test lift. In the 2 and 10 second delay conditions there was a 2 or 10 second delay, respectively, between the release of the object after the last practice lift, and the test lift. Greater peak grip force was produced for the first lift compared to the subsequent practice lifts. In the 0 second delay condition, the peak grip force used in the test lift was similar to the last practice lift. As the delay increased to 10 seconds, the peak grip forces used were similar to that of the first lift. Even after a 2 second delay the peak grip force was greater than that of the last practice lift. Peak torque also followed these same patterns. The present results suggest that the haptic representation of object mass is short-lived (< 2 s) and has a duration and decay similar to visual iconic memory.

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 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)0.001
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: none
Teacher disagreement score0.643
Threshold uncertainty score0.116

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.142
GPT teacher head0.324
Teacher spread0.182 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations32
Published2009
Admission routes2
Has abstractyes

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