On integration of a novel minimally invasive surgery robotic system
Bibliographic record
Abstract
Today's laparoscopic surgeon performs laparoscopic surgery by inserting two or three long tools into the patient's abdominal. Surgeon relies on the image captured by a laparoscope that is also inserted into the patient's abdominal. It is common to have a surgical assistant holding the laparoscope and taking directions from the main surgeon on how to move it to keep the surgical tools within the view. However, timely, accurate, and stable adjustments of the laparoscope cannot be guaranteed in lengthy operations due to the fatigue of human assistant. We proposed a novel new design by replacing the human assistant with a spherical wrist mechanism robot. In addition, for developing a fully surgeon-based automatic integrated system, an automatic tracking and gesture recognizing sub-system is developed. The automatic tracking sub-system tracks the tip of a surgical tool and moves the laparoscope holding robot to keep the tool within the camera view. The gesture recognizing sub-system helps surgeon retrieve critical medical records of the patient instantly by recognizing surgical tool gestures performed by surgeon
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".