OMASTAR Optimal Magnetic Actuation System Arrangement
Bibliographic record
Abstract
Microrobots and other miniature robots are able to access millimeter-sized spaces and thus have the potential to solve many challenging problems in healthcare. However, clinical adoption of these robots is rare as these systems are often difficult to scale up. One such issue arises from the actuation systems used to remotely control magnetic microrobots, which tend to be bulky and obstruct the surgeons' workspaces. They also do not guarantee wide ranges of magnetic fields and forces in a large patient-sized workspace. In this paper, we present the design of a permanent magnet-based actuation system that fits within a 40 cm cube of space under an operating table. We also formulate a new set function maximization-based approach for efficiently designing E-optimal magnet arrangements with off-the-shelf convex solvers. Our optimization method is evaluated with synthetic data and a proof-of-concept of the system is simulated.
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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 | 0.000 |
| 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 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".