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Record W2038173552 · doi:10.1088/0960-1317/18/6/065009

Planar frictional micro-conveyors with two degrees of freedom

2008· article· en· W2038173552 on OpenAlexaff
Byron Shay, Ted Hubbard, Marek Kujath

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPlanarFabricationRotational speedMechanical engineeringActuatorEngineeringMaterials scienceElectrical engineeringComputer science

Abstract

fetched live from OpenAlex

The design, fabrication and operation of planar frictional micro-conveyors with two degrees of freedom (2-DOF) were investigated. The frictional micro-conveyors consisted of two parts: a driving unit and a mobile plate. The driving unit was comprised of thermal actuators which were attached to inverted feet. The plate was in constant frictional contact with the feet surfaces and by properly sequencing the motion of the feet, the plate moved with stepwise advances. Two different 2-DOF designs were constructed: an X–θ conveyor capable of linear and rotational yaw motions and an X–Y conveyor capable of planar translation. Both types of micro-conveyors were fabricated using 10 µm thick silicon-on-insulator technology. The X–θ driving unit's size was 580 × 960 µm2 and it moved a 700 × 380 µm2 plate. The X–Y driving unit's size was 720 × 720 µm2 and it moved a 530 × 530 µm2 plate. The X–θ conveyor was capable of moving the plate at a linear speed of up to 33 µm s−1 and a rotational speed of up to 7° s−1. The X–Y conveyor was capable of translating the plate at a speed of 20 µm s−1 along either axis. The conveyors were able to transport loads in excess of 850 µg.

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 score0.049
Threshold uncertainty score0.613

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 head0.007
GPT teacher head0.174
Teacher spread0.167 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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