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Record W3148662896 · doi:10.1109/iros.2011.6048742

Micro-scale propulsion using multiple flexible artificial flagella

2011· article· en· W3148662896 on OpenAlexafffund
John Singleton, Eric Diller, Tim Andersen, Stéphane Régnier, Metin Sitti

Bibliographic record

Venue2011 IEEE/RSJ International Conference on Intelligent Robots and Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPropulsionFlagellumScale (ratio)Aerospace engineeringComputer scienceBiomimeticsMarine engineeringArtificial intelligenceEngineeringGeologyPhysics

Abstract

fetched live from OpenAlex

A new actuation principle which permits omnidirectional steering for a swimming robot using a magnetic resonance imaging scanner is presented. The robot fish is made of a ferromagnetic head and a flexible tail. It is actuated by transverse oscillating magnetic gradients. The swimming performances of the robot fish are studied for varying tail length as well as varying actuation frequency and amplitude. Through a dimensional analysis, the important parameters influencing the swimming gait are identified and the mechanism of actuation is better understood. Considering the scaling of forces, this dimensional analysis leads us to believe that in the future the height and width of the fish robot could be miniaturised to sub-millimetre scale.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.128
GPT teacher head0.290
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2011
Admission routes2
Has abstractyes

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