A New Medical Parallel Robot and Its Static Balancing Optimization
Why this work is in the frame
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Bibliographic record
Abstract
The preoperative procedure for treating peripheral arterial disease requires 3D mapping of the blood vessel of interest. Because the available technologies are costly and invasive, and have an iodizing effect, new 3D imaging systems are being developed from ultrasound scanning technology using a robot as the probe manipulator. The authors of this paper have designed a new parallel robot along these lines. In response to the great concern for safety generated by the use of robots in medicine, we present a new approach for static balancing to enhance the safety of the proposed robot. Because total balancing is not practical for this device, the approach we have chosen is an optimization based on the addition of torsion springs on the actuated and the passive revolute joints. The optimization consists of a sequence of objectives, which are met using a linear programming technique, since the equations of torques and forces are linear with respect to the unknown variables.
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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 | 0.001 | 0.000 |
| 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 it