Millimeter-Scale Magnetically Actuated Robotic Tools for Surgery and Cell Manipulation
Bibliographic record
Abstract
Small scale robots are precise end-effectors that can manipulate objects with a high degree of accuracy. Many surgical and on-chip tasks can be performed by manipulating these robots in their dedicated environments. Mobile untethered surgical robots are an attractive research area because of their ability to maneuver inside small and constrained environments and perform tasks that were previously considered infeasible. These robots enable us to make surgery minimally invasive. Surgeons can drill a hole in your skull and insert the tools inside the ventricles from where they can navigate their way to either cut or grasp tissue. Because these robots are too small for electronics and on-board power, they are often actuated remotely using magnetic fields as these field can penetrate most environments and are relatively safe for biological organisms. This makes them an ideal tool to use inside the human body and for on-chip applications. Magnetic tools can be developed and placed inside microfluidic platforms for cell manipulation such as sorting and stimulation. Both on-chip and mobile devices are explored in this thesis focusing on applications related to cell manipulation as well as surgical tools. Specifically, this thesis involves a discussion on the development of a pair of micro-surgical scissors for cutting of soft tissues as well as a magnetically oscillating beam that can be used to apply shear stress to cells and used for cell sorting purposes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".