An image‐guided automated robot for MRI breast biopsy
Bibliographic record
Abstract
BACKGROUND: The IGAR (Image-guided Automated Robot) is a robotic platform capable of performing highly accurate clinical interventions under image guidance. The IGAR is unique in that it demonstrates MRI compatibility and maintains safe operation, adequate shielding, high image quality, and accurate robotic control even while in an imaging environment. The IGAR is initially intended for breast biopsy. METHODS: Tests for projectile hazards, heating, signal-to-noise ratio loss, and geometric distortion were used to demonstrate MR compatibility. Accuracy and repeatability of the robotic system were tested on benchtop models to establish a baseline of precision. RESULTS: The IGAR averaged an accuracy of 0.34 mm and a repeatability of 0.2 mm. There was no significant distortion attributable to the robot, no projectile risk, and no unacceptable levels of heating. CONCLUSION: The IGAR system is safe and effective in an MRI environment Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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".