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Record W2053254070 · doi:10.1109/iros.2006.282628

Design of a Micro-Gripper and an Ultrasonic Manipulator for Handling Micron Sized Objects

2006· article· en· W2053254070 on OpenAlexaff
Felix Beyeler, Dominik J. Bell, Bradley J. Nelson, Yu Sun, Adrian Neild, Stefano Oberti, Jürg Dual

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicroelectromechanical systemsUltrasonic sensorGrippersMaterials scienceFabricationRoboticsRobotNanotechnologyProcess (computing)Mechanical engineeringComputer scienceAcousticsEngineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

This work reports on a system consisting of a MEMS (microelectromechanical system) gripper and an ultrasonic manipulator. The gripper is electrostatically actuated and includes an integrated force sensor measuring the gripping force. The device is monolithically fabricated using a silicon-on-insulator (SOI) fabrication process. The resolution of the force sensor is in the sub-micronewton range and, therefore, provides feedback of the forces that dominate the micromanipulation processes. A MEMS ultrasonic device is described which aligns small objects such as biological cells prior to manipulation with the gripper. The concept is demonstrated with polymer spheres, glass spheres and Hela cancer cells, thus providing a useful tool in micro-robotics and biological research

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.379

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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 teacher head, 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

Citations36
Published2006
Admission routes1
Has abstractyes

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