MétaCan
Menu
Back to cohort
Record W4400488043 · doi:10.1109/lra.2024.3426385

Breathing Compensation in Magnetic Robotic Bronchoscopy via Shape Forming

2024· article· en· W4400488043 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Robotics and Automation Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsMcMaster University
FundersEngineering and Physical Sciences Research Council
KeywordsCompensation (psychology)BronchoscopyBreathingMedicineComputer scienceComputer visionArtificial intelligencePsychologyAnatomyRadiologyPsychoanalysis

Abstract

fetched live from OpenAlex

Despite the increased interest in robotic systems designed for bronchoscopy, the influence of the bronchial tree dynamics remains relatively unexplored. To enable robotic solutions to perform successful autonomous navigations whilst minimizing contact with the internal anatomy, they must be capable of adapting to ongoing geometric changes caused by the respiratory cycle. In this letter, we introduce a method for parameterizing these cyclic changes and present a flexible magnetic robotic catheter design that adapts its shape dynamically. Three bronchial branches (up to 4th generation bronchioles) with diverse shapes were investigated to examine the feasibility and efficacy of this approach. Reference anatomical geometry was taken from an open-source dynamic computed tomography patient dataset, and was evaluated over the breathing cycle to develop patient- and branch-specific magnetic catheter profiles and associated time-varying external magnetic fields. The system was demonstrated using dynamic Helmholtz coil actuation and showed a mean error in replicating the centerline of each of the three branches over the entire navigation of 2.1 mm, 1.4 mm, and 1.9 mm respectively.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.650

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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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