Graphical Reproduction of Tactile Information of Embedded Lumps for MIS Applications
Bibliographic record
Abstract
Promising results of minimally invasive surgery (MIS) in the last two decades have been the main incentive of numerous researches to conquer some of the drawbacks of this procedure. Restoring the missing tactile information, especially the tissue palpation, is a significant enhancement in MIS capabilities. Tissue palpation is particularly important and commonly used in locating the embedded lumps. The present study is inspired by this essential limitation in MIS procedure and is aimed at developing a system to reconstruct the lost palpation capability of surgeons in an effective way. Having collected necessary information on the size and location of the hidden features using MIS graspers equipped with tactile sensors, we can process the information and graphically represent them to the surgeon. Therefore, the proposed system allows the surgeons to observe the presence or absence, location and approximate size of hidden lumps simply by grasping the target organ with smart endoscopic grasper. It is shown that using one array of the sensing elements; the proposed system can extract lump information including size and longitudinal location. The experimental results on the prototyped MIS graspers represented by graphical images conform to those of the finite element models.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".