The role of visual and direct force feedback in robotics‐assisted mitral valve annuloplasty
Bibliographic record
Abstract
BACKGROUND: The objective of this work was to determine the effect of both direct force feedback and visual force feedback on the amount of force applied to mitral valve tissue during ex vivo robotics-assisted mitral valve annuloplasty. METHODS: A force feedback-enabled master-slave surgical system was developed to provide both visual and direct force feedback during robotics-assisted cardiac surgery. This system measured the amount of force applied by novice and expert surgeons to cardiac tissue during ex vivo mitral valve annuloplasty repair. RESULTS: The addition of visual (2.16 ± 1.67), direct (1.62 ± 0.86), or both visual and direct force feedback (2.15 ± 1.08) resulted in lower mean maximum force applied to mitral valve tissue while suturing compared with no force feedback (3.34 ± 1.93 N; P < 0.05). CONCLUSIONS: To achieve better control of interaction forces on cardiac tissue during robotics-assisted mitral valve annuloplasty suturing, force feedback may be required.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".