Control of Movement Variability and the Regulation of Limb Impedance
Bibliographic record
Abstract
Humans routinely make movements to targets that have different accuracy requirements in different directions. Examples extend from everyday occurrences such as grasping the handle of a coffee cup to the more refined instance of a surgeon positioning a scalpel. The attainment of accuracy in situations such as these might be related to the nervous system's capacity to regulate the limb's resistance to displacement, or impedance. To test this idea, subjects made movements from random starting locations to targets that had shape-dependent accuracy requirements. We used a robotic device to assess both limb impedance and patterns of movement variability just as the subject reached the target. We show that impedance increases in directions where required accuracy is high. Independent of target shape, patterns of limb stiffness are seen to predict spatial patterns of movement variability. The nervous system is thus seen to modulate limb impedance in entirely predictable environments to aid in the attainment of reaching accuracy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".