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Record W3105263399 · doi:10.1002/mma.6990

Some weighted quadrature methods based upon the mean value theorems

2020· article· en· W3105263399 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

VenueMathematical Methods in the Applied Sciences · 2020
Typearticle
Languageen
FieldMathematics
TopicIterative Methods for Nonlinear Equations
Canadian institutionsUniversity of Victoria
FundersAlexander von Humboldt-Stiftung
KeywordsMathematicsQuadrature (astronomy)Clenshaw–Curtis quadratureTanh-sinh quadratureGauss–Jacobi quadratureGauss–Kronrod quadrature formulaWeighted arithmetic meanApplied mathematicsMean valueClass (philosophy)Mathematical analysisGaussian quadratureNyström methodIntegral equationStatisticsComputer science

Abstract

fetched live from OpenAlex

In this paper, a class of weighted quadrature methods is introduced for smooth functions based upon the use of the mean value theorems. These new quadrature rules are also treated in a systematic approach involving formal series expansion. The convergence analysis of the proposed method is studied here for both the non‐weighted and the weighted cases. Some potential areas and directions for extensions and applications of the results, which are presented in this paper, are also indicated.

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)0.039
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
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 score0.148
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0390.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.485
Teacher spread0.286 · 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