New tactile sensing system for minimally invasive surgical tumour localization
Bibliographic record
Abstract
BACKGROUND: Minimally invasive surgery (MIS) suffers from the inability to directly palpate organs for tumour localization. A tactile sensing system (TSS), consisting of a probe and a visualization interface, was developed to present an active pressure map of the contact surface to locate tumours during MIS. METHODS: The TSS performance was compared to MIS graspers to locate occult 10 mm phantom tumours in ex vivo bovine liver and ex vivo porcine lung. Performance assessment included applied pressure, localization distance and accuracy. RESULTS: The TSS realized a relative 71% reduction in maximum applied pressure and a 31% increase in detection accuracy in liver tissue (when compared to MIS graspers) and demonstrated no significant differences in performance when palpating lung tissue. CONCLUSIONS: The TSS may help surgeons to identify occult tumours during surgery by restoring some of the haptic information lost during MIS.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".