The Control Strategy for Degrees of Freedom in Remote Prehension with a Tool
Bibliographic record
Abstract
Constructing movement couplings is essential for decreasing degrees-of-freedom for a compound movement that requires coordination over a multiple segments. Angular movements of joints in the upper limbs are examined, the pattern of movement couplings between prehension performed with the hands (natural prehension) and with a simple grasper held in the hands (remote prehension). In remote prehension, the shoulder and elbow joint are tightly associated with a clear in-phase joint to joint movement; the elbow and wrist display both anti- and in-phase movements due to the change of initial configuration of the upper limb when holding a tool. In contrast, the shoulder-elbow bond is mixed in natural prehension, but the elbow and wrist bond is predominant with an anti-phase pattern. With diversity for joint couplings, the movement consistency of the hinge is preserved with relatively smaller path variability. Results support the end-point control notion, i.e. movement is controlled by extrinsic coordinates close to the end-effectors of the movement system.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".