Bibliographic record
Abstract
There has been increasing use of robotic surgery over the years, as it has evolved as an improvement over minimally invasive surgery (MIS), where a surgeon can use a tele-manipulator to operate on a patient. Magnetic resonance imaging (MRI) has become the leading form of image acquisition due to its ability to produce high resolution images during robotically assisted MIS. However, the MRI scanner places conditions on the robots that allow only certain compatible actuation methods used in the robotic system to negate large interference that hinders the image quality. The current review focused on the four main MRI-compatible actuation mechanisms: hydraulic, pneumatic, piezoelectric, and shape memory alloy. This review mainly discussed signal-to-noise ratio (SNR) reduction, performance, and limitations from the recent publications on MRI-compatible robotic surgeries. Favorable MRI compatibility with low SNR reduction, performance, and simple implementation was observed to be the most important characteristics of a proper actuation mechanism for MRI robotic surgeries. After reviewing each approach, it was concluded that shape memory alloy, despite having a form of limitation, demonstrated to be more favorable compared to other actuation methods because of factors such as low cost, negligible SNR reduction, and high-power output for medical interventions
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".