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Record W2749348682

Sensory modalities influence on hand perception

2015· article· en· W2749348682 on OpenAlexaff
Lara A. Coelho, Claudia L. R. Gonzalez

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsStylusProprioceptionPerceptionTask (project management)PsychologyModalitiesRepresentation (politics)Hand positionCognitive psychologyComputer visionComputer scienceCommunicationArtificial intelligenceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Previous research has found that the perception of one's hands is inaccurate. Furthermore, this inaccuracy has certain distinguishable patterns including an overestimation of hand width and an underestimation of finger length. The aim of the present study is to investigate the influence of vision to this distorted perception. Participants were required to place their hand underneath a glass tabletop and point to ten locations on their hand when their hand was visible (real condition) or hidden from view (perception condition). Participants had vision throughout the task (Group 1) or wore a blindfold during the perception portion of the task (Group 2). They completed the task by pointing with their own finger or with a wooden stylus, to investigate if proprioceptive feedback of the pointing hand influenced hand perception. The task was completed with both the right and left hands. Results replicated previous findings of an overestimation of hand width and underestimation of finger length, but participants were more accurate when vision was unavailable (Group 2). This finding suggests that vision interferes with hand representation. Proprioceptive feedback of the pointing hand played only a minor role with slightly more accurate representation when pointing with the finger. Finally, when compared to the left hand, right hand estimates were more distorted regardless of visual availability and pointer effector (finger or stylus).

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.856
Threshold uncertainty score0.318

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 integrity0.0000.000
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 head0.039
GPT teacher head0.267
Teacher spread0.228 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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