Motor Control: Theories, Experiments, and Applications
Bibliographic record
Abstract
Motor control has established itself as an area of scientific research characterized by a multi-disciplinary approach. Scientists working in the area of control of voluntary movements come from different backgrounds including but not limited to physiology, physics, psychology, mathematics, neurology, physical therapy, computer science, robotics, and engineering. One of the factors slowing progress in the area has been the lack of communication among researchers representing all these disciplines. A major objective of the curreent book is to overcome this deficiency and to promote cooperation and mutual understanding among researchers addressing different aspects of the complex phenomenon of motor coordination. The book offers a collection of chapters written by the most prominent researchers in the field. Despite the variety of approaches and methods, all the chapters are united by a common goal: To understand how the central nervous system controls and coordinates natural voluntary movements. This book will be appreciated as a major reference by researchers working in all the subfields that form motor control. It can also be used as a supplementary reading book for graduate courses in such fields as kinesiology, physiology, biomechanics, psychology, robotics, and movement disorders. In one concise volume, Motor Control presents the diversity of the research performed to understand human movement. Deftly organized into 6 primary sections, the editors, Dr Frederic Danion and Dr Mark Latash, have invited the who's who of specialists to write on: MotorControl: Control of a Complex; Cortical Mechanisms of Motor Control; Lessons from Biomechanics; Lessons from Motor Learning and Using Tools; Lessons from Studies of Aging and MotorDisorders; and Lessons from Robotics Motor Control will quickly become the go-to reference for researchers in this growing field. Researchers from mechanics and engineering to psychology and neurophysiology, as well as clinicians working in motor disorders and rehabilitation, will be equally interested in the pages contained herein.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".