MétaCan
Menu
Back to cohort
Record W2072317137 · doi:10.1504/ijmrs.2013.057171

Modelling, analysis and experiments of a screw propelling capsule robot

2013· article· en· W2072317137 on OpenAlex
Huajin Liang, Yisheng Guan, Zhenneng Yin, Hong Zhang

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

VenueInternational Journal of Mechanisms and Robotic Systems · 2013
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsUniversity of Alberta
FundersChinese Academy of Sciences
KeywordsCrawlingRobotThrustCapsuleComputer sciencePropulsionMechanism (biology)SimulationMechanical engineeringEngineeringArtificial intelligencePhysicsAerospace engineeringGeologyBiologyAnatomy

Abstract

fetched live from OpenAlex

Active locomotion has been a challenge in the research and development of capsule endoscopies for diagnosis and therapy inside gastrointestinal tracts. As one prospective solution to the active locomotion of capsule robots, screw propelling has many important issues to be addressed in both theory and practice. In this paper, we build one- and two-dimensional models of screw propelling and make quantitative analysis to find the relationship between the axial thrust force and the geometric parameters of the screws, for optimal design of the actuation mechanism with high efficiency of propulsion. A few prototypes of the capsule robots are developed and a series of contrast experiments are conducted to verify the theoretical models and analysis. The effectiveness of active drive of capsule robots by screw propelling has been preliminarily shown by the experiments with the prototypes crawling in a tube.

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: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.308

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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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