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Record W2124685884 · doi:10.1177/0278364905055594

Fundamental Principles and Issues of High-speed Piezoactuated Three-legged Motion for Miniature Robots Designed for Nanometer-scale Operations

2005· article· en· W2124685884 on OpenAlexaff
Sylvain Martel

Bibliographic record

VenueThe International Journal of Robotics Research · 2005
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsPolytechnique Montréal
FundersMassachusetts Institute of Technology
KeywordsRobotNanometreScale (ratio)ThroughputRange (aeronautics)Computer sciencePosition (finance)Control engineeringSimulationEngineeringWirelessAerospace engineeringArtificial intelligencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

One of the important aspects in the development of high-throughput platforms based on a fleet of scientific instruments in the form of miniature wireless robots designed for fast operations at the nanometer-scale, is the conception of an embedded locomotion system capable of fast displacements between two successive locations while being accurate enough to position the robot within the range of the embedded instrument, typically within a few tenths of nanometers. This paper describes not only the fundamental principles of the locomotion method and mechanisms but the main constraints, challenges, and environmental conditions that must be taken into account in the implementation of such a system. Preliminary experimental results show the validity of this approach.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.057
GPT teacher head0.331
Teacher spread0.274 · 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 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

Citations28
Published2005
Admission routes1
Has abstractyes

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