MétaCan
Menu
Back to cohort
Record W4254219847 · doi:10.1063/1.4874306.1

10.1063/1.4874306.1

2014· dataset· en· W4254219847 on OpenAlexaff
Eric Diller, Zhuang Jiang, Guo Zhan Lum, Matthew R. Edwards, Metin Sitti

Bibliographic record

VenueDefault Digital Object Group · 2014
Typedataset
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMillimeterRoboticsMagnetic fieldRobotPropulsionDeformation (meteorology)Reynolds numberScalingScale (ratio)Measure (data warehouse)Computer scienceMechanical engineeringPhysicsAcousticsArtificial intelligenceEngineeringAerospace engineeringMechanicsMathematicsGeometryOpticsMeteorologyTurbulence

Abstract

fetched live from OpenAlex

We have developed a millimeter-scale magnetically driven swimming robot for untethered motion at mid to low Reynolds numbers. The robot is propelled by continuous undulatory deformation, which is enabled by the distributed magnetization profile of a flexible sheet. We demonstrate control of a prototype device and measure deformation and speed as a function of magnetic field strength and frequency. Experimental results are compared with simple magnetoelastic and fluid propulsion models. The presented mechanism provides an efficient remote actuation method at the millimeter scale that may be suitable for further scaling down in size for micro-robotics applications in biotechnology and healthcare.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.752
Threshold uncertainty score0.831

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.2480.515

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 head0.006
GPT teacher head0.221
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueDefault Digital Object GroupSame topicMicro and Nano RoboticsFrench-language works237,207