Design of a Minimally Invasive Lung Tumor Localization Device
Bibliographic record
Abstract
This paper describes the design, analysis, and experimental validation of a novel minimally invasive instrument for lung tumor localization. The instrument end effector is a two-degree of freedom lung tissue palpator. It allows for optimal tissue palpation to increase useful sensor feedback by ensuring sensor contact, and prevents tissue damage by uniformly distributing pressure on the tissue. Finite element analysis was used to guide the design process, resulting in a final design that could achieve a factor of safety of 4 for a 20 N force acting on the end effector—the approximate weight of a human lung. Validation experiments were conducted on a prototype instrument to assess its articulation and load-carrying capacity. The end effector design allows for the inclusion of ultrasound, tactile, and kinesthetic sensors. It is expected that this device will form the basis for robotics-assisted palpation and increase the likelihood of positive tumor localization.Copyright © 2012 by ASME
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".