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Record W2142653499 · doi:10.1109/mcs.2006.252839

DynaFlexPro for Maple

2006· article· en· W2142653499 on OpenAlexaboutno aff
Rajankumar Bhatt, Venkat Krovi

Bibliographic record

VenueIEEE Control Systems · 2006
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMapleToolboxComputer scienceSymbolic computationGraphProgramming languageControl engineeringTheoretical computer scienceSoftware engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

DynaFlexPro (DFP), released in the middle of 2005 by MotionPro, Inc. is marketed by MapleSoft, Inc., of Waterloo, Ontario. DFP is a Maple toolbox that allows control engineers to symbolically create mathematical models for analyzing the dynamic behavior of large articulated multibody systems. DFP combines graph-theoretic modeling techniques with Maple's computer-algebra manipulation capabilities to automatically create the symbolic equations of motion (EOMs)

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.353
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0030.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.3530.221

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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.

Study designNot applicable
Domainnot available
GenreSoftware

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

Citations3
Published2006
Admission routes1
Has abstractyes

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