Diamagnetically stabilized levitation control of an intraluminal magnetic capsule
Bibliographic record
Abstract
Controlled navigation promotes full utilization of capsule endoscopy for reliable real-time diagnosis in the gastrointestinal (GI) tract, but intermittent natural peristalsis can disturb the navigational control, destabilize the capsule and take it out of levitation. The focus of the present work was to develop an economical and effective real-time magnetic capsule-guiding system that can operate in the presence of naturally existing peristalsis while retaining navigational control. A real-size magnetic navigation system that can handle peristaltic forces of up to 1.5 N was designed utilizing the computer-aided design (CAD) system Maxwell 3D (Ansoft, Pittsburg, PA) and was verified using a small-size physical experimental setup. The proposed system contains a pair of 50 cm diameter, 10,000-turn copper electromagnets with a 10 cm x 10 cm ferrous core driven by currents of up to 300 A and can successfully maintain position control over the levitating capsule during peristalsis. The addition of bismuth diamagnetic casing for stabilizing the levitating capsule was also studied. A modeled magnetic field around the diamagnetically cased permanent magnet was shown to be redistributed aligning its interaction with the external electromagnets, thus stabilizing the levitating capsule. In summary, a custom-designed diamagnetically facilitated capsule navigation system can successfully steer an intraluminal magnet-carrying capsule.
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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 | 0.000 |
| 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 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".