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Record W2084023235 · doi:10.1115/1.4005931

Galerkin Approximations for Higher Order Delay Differential Equations

2012· article· en· W2084023235 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Computational and Nonlinear Dynamics · 2012
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsUniversity of Waterloo
FundersIndian Institute of Technology Kharagpur
KeywordsGalerkin methodMathematicsNonlinear systemDelay differential equationMathematical analysisLagrange multiplierScalar (mathematics)Partial differential equationBoundary value problemApplied mathematicsDifferential equationMathematical optimizationPhysicsGeometry

Abstract

fetched live from OpenAlex

In this work, Galerkin approximations are developed for a system of n first order nonlinear delay differential equations (DDEs) and also for an nth order nonlinear scalar DDE. The DDEs are converted into an equivalent system of partial differential equations of the same order along with the nonlinear boundary constraints. Lagrange multipliers are then introduced and explicit expressions for the Lagrange multipliers are derived to enforce the nonlinear boundary constraints. To illustrate the method, comparisons are made between the numerical solution of nonlinear DDEs and its Galerkin approximations for different parameter values.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.421
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.064
GPT teacher head0.363
Teacher spread0.299 · 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