Model Averaging and Input Transformation for 3D Needle Steering
Bibliographic record
Abstract
In this paper, a duty-cycle-based method is proposed for needle steering in 3D. The paper models the continuous 3D needle steering problem as a four-mode switching system and provides a new average-based formulation to transform the continuous input into a switching sequence. In this structure, the needle tip deflection control system is decomposed to two different 2D subsystems. Each subsystem has its own input, for which a controller can be designed to adjust a switching duty cycle. The duty cycles from the two subsystems are then combined to provide an axial needle rotation command to control the needle deflection in 3D. In order to show the application of the proposed formulation, robust sliding mode technique is employed to design controllers for each subsystem and, thus for the total system in 3D. The controllers are designed to be robust with respect to uncertainties in the value of the needle path curvature and to deal with measurement limitations. The performance of the proposed framework is shown by performing experiments in different scenarios.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".