Optimizing port placement for robot‐assisted minimally invasive cardiac surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Proper placement of ports during robot-assisted endoscopic surgery is critical to the success of the procedure. In current practice, port placement methods do not consider the ability of the robot to manoeuvre the tools. METHODS: This paper proposes to choose the best port location such that the performance of the robot is maximized. The Global Conditioning Index (GCI) is used to optimize port placement when using the da Vinci((R)) surgical system during cardiac surgery. RESULTS: The results show that, due to a singularity at the remote centre of motion, higher performance is obtained the further away the port is from the workspace. When compared to the ports selected by an expert surgeon, our results show that it is possible to increase robot performance by at least 29% for the left arm of the robot. CONCLUSIONS: Selecting an adequate port location can improve robot performance and ensure that the instruments reach the surgical site.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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