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Record W3132259949 · doi:10.1088/1402-4896/abe066

A cubic B-spline collocation method with new approximation for the numerical treatment of the heat equation with classical and non-classical boundary conditions

2021· article· en· W3132259949 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

VenuePhysica Scripta · 2021
Typearticle
Languageen
FieldMathematics
TopicDifferential Equations and Boundary Problems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDiscretizationCollocation methodMathematicsCollocation (remote sensing)PiecewiseInterpolation (computer graphics)Applied mathematicsSpline interpolationMathematical analysisB-splineConvergence (economics)Stability (learning theory)Boundary value problemComputer scienceDifferential equationOrdinary differential equation

Abstract

fetched live from OpenAlex

Abstract In this paper, a cubic B-spline collocation method equipped with new approximations for second-order derivatives is used to approximate the solution of the heat equation. This technique depends on the typical finite difference scheme to discretize the time derivative while cubic B-splines are utilized as interpolation functions in the space dimension. The key advantage of using this approach is that the solution is obtained as a piecewise continuous function empowering one to find approximation at any desired location of the domain. The stability and convergence analysis of the presented method are studied rigorously. The capability of the scheme is checked by some test problems. The effectiveness and exactness of the proposed method are confirmed by computing the error norms. Numerical results are contrasted with some existing numerical schemes to exhibit the predominance of our scheme.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.356

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 head0.065
GPT teacher head0.322
Teacher spread0.258 · 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