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Record W1968809237 · doi:10.2466/pms.2002.95.3f.1129

Jaw and Finger Movement Accuracy under Visual and Nonvisual Feedback Conditions

2002· article· en· W1968809237 on OpenAlexaff
Luc F. De Nil, Sophie J. Lafaille

Bibliographic record

VenuePerceptual and Motor Skills · 2002
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsVisual feedbackArticulatorComputer scienceIndex fingerMovement (music)Computer visionModalitiesPhysical medicine and rehabilitationArtificial intelligencePsychologyCommunicationCognitive psychologyMedicineOrthodontics

Abstract

fetched live from OpenAlex

The present study revisited the issue whether the presence of added visual feedback differentially affects the accuracy of finger and jaw movements. 15 men were instructed to move either the index finger on the dominant (right) hand, or the jaw, to a predefined target position with the highest precision possible. During execution of the task, on-line visual feedback of the moving articulator was either present or removed. In contrast to previous findings, significant improvement was observed for both finger and jaw movements in the visual feedback condition. Movement error in the nonvisual condition was proportionally greater for finger than for jaw movements which may have reflected a speed-accuracy trade-off because finger movements in the nonvisual condition were executed significantly faster than those of the jaw. The present findings support the beneficial effects of adding visual feedback during dynamic oral and finger movements that require a high spatial precision. Such findings support current methods of clinical intervention in speech-language pathology anl other disciplines. Furthermore, the results contribute to our understanding of the role of various modalities of feedback during motor execution.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.904

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)0.0010.000

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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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

Citations12
Published2002
Admission routes1
Has abstractyes

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