Design and Fabrication of a Novel Teardrop-Shaped Magnetically Guided Hollow Robot for Potential Capsule Application
Bibliographic record
Abstract
Wireless capsule robot technology is promising because it is minimally invasive. Magnetically guided capsule robots, in particular, have garnered significant attention because they allow for noninvasive or less invasive remote control of endoscopes within the body. However, miniaturizing capsule robots remains a challenge, especially for applications within the urinary system. This article proposed a novel teardrop-shaped magnetically guided capsule robot, which has several salient features. First, a coupled design strategy was implemented for the actuator and body, reducing the overall size of the device. Second, a bio-inspired teardrop shape was utilized in the design to minimize resistance (RES) as the robot moves within the body, with the design process supported by the finite element analysis, regression model, and the Taguchi robust design technique. Third, a special 3-D printing method was employed to fabricate a prototype of the robot, taking advantage of its capability to print micro/nanometer features. An in vitro experiment was conducted to validate the effectiveness and potential of the capsule robot system.
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 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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".