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Record W2146373240 · doi:10.1088/0967-3334/30/8/003

Diamagnetically stabilized levitation control of an intraluminal magnetic capsule

2009· article· en· W2146373240 on OpenAlexaff
Michael Lam, Martin P. Mintchev

Bibliographic record

VenuePhysiological Measurement · 2009
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersOlympus
KeywordsLevitationCapsuleMagnetic levitationElectromagnetPeristalsisMagnetEngineeringMechanical engineeringAnatomyMedicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.285
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2009
Admission routes1
Has abstractyes

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