Suitability of Two Models of Torque Feedback for Performing a Robot-Assisted Circular Tracing Task
Bibliographic record
Abstract
In robot-assisted surgery, haptic devices as hand controllers play an important role in the surgeon's ability of manipulating tissues. Most research activities have focused on providing force feedback as haptic information. Considering a circular tracing task, we presented two models of torque feedback. On a Virtual Reality simulator of neuroArm, a robotic system for microscopic neurosurgery, we investigated the suitability of these models for rendering torque feedback of each rotational degree-of-freedom. Without sacrificing translational and rotational motion ranges, we verified that the device PHANToM Premium 1.5/6DOF is adequate as a hand controller of neuroArm to replace the modified version of PHANToM Premium 1.5 interfacing originally with neuroArm. Using the device PHANToM Premium 1.5/6DOF, our preliminary results yielded a suitability of both models of torque feedback for performing a circular tracing task assisted by neuroArm.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".