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Record W2037908975 · doi:10.1002/rob.1070

The constant‐Jacobian method for kinematics of a three‐DOF planar micro‐motion stage

2002· article· en· W2037908975 on OpenAlexaff
Wenjun Zhang, Jin Zou, L. G. Watson, Wanqing Zhao, Guo-Wei Zong, Shusheng Bi

Bibliographic record

VenueJournal of Robotic Systems · 2002
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsJacobian matrix and determinantKinematicsPlanarConstant (computer programming)Control theory (sociology)Motion (physics)Parallel manipulatorComputer scienceMathematicsPhysicsControl (management)Artificial intelligenceClassical mechanicsApplied mathematicsComputer graphics (images)

Abstract

fetched live from OpenAlex

Abstract This paper concerns the development of a class of devices that generate end‐effector motion in the range of less than 100 μm and with sub‐nanometer resolution; in particular, a parallel manipulator configuration that generates a planar x‐y‐γ motion is considered. The parallel manipulator is implemented as a compliant mechanism. A problem with parallel manipulators is that the forward kinematics is usually too complex, which can hinder the implementation of advanced control algorithms. The contribution of this paper is that a simple method, called the constant‐Jacobian (CJ) method, is developed based on the pseudo‐rigid body (PRB) approach to compliant mechanisms. The experiment validates the CJ method. © 2002 John Wiley & Sons, Inc.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.029
GPT teacher head0.243
Teacher spread0.214 · 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

Citations68
Published2002
Admission routes1
Has abstractyes

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