MétaCan
Menu
Back to cohort
Record W2156377059 · doi:10.1115/1.4028933

Comparative Analysis of a Redundant Pentapod Parallel Kinematic Machine

2014· article· en· W2156377059 on OpenAlexafffund
Arta Alagheband, Masih Mahmoodi, James K. Mills, B. Benhabib

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2014
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of New BrunswickUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkspaceKinematicsStiffnessMechanism (biology)Tilt (camera)Computer scienceStewart platformParallel manipulatorMechanical engineeringEngineeringRobotStructural engineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Parallel kinematic mechanisms (PKMs) provide high stiffness and compact structures that are suitable for a large number of applications, including 5-axis milling. This paper presents a new pentapod-based PKM with an additional redundant degree-of-freedom (DOF) capable of reaching platform tilt angles of at least 90 deg over a large workspace. The proposed new PKM has a 6DOF 4 × SPRR + 1 × PSPR architecture. It is compared herein to Metrom® Pentapod as well as to several other pertinent PKMs in terms of workspace and dynamic stiffness. It is shown that the proposed mechanism can yield a tangibly larger workspace volume, when compared to those PKMs, while maintaining its high stiffness characteristics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.011
GPT teacher head0.230
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations17
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Mechanisms and RoboticsSame topicRobotic Mechanisms and DynamicsFrench-language works237,207