Jaw and Finger Movement Accuracy under Visual and Nonvisual Feedback Conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".