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Record W2799315072 · doi:10.1002/mma.4945

Well‐posed fractional calculus operator: Obtaining new transformations formulas involving Gauss hypergeometric functions with rational quadratic, cubic, and higher degree arguments

2018· article· en· W2799315072 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMathematical Methods in the Applied Sciences · 2018
Typearticle
Languageen
FieldMathematics
TopicIterative Methods for Nonlinear Equations
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMathematicsHypergeometric functionGaussQuadratic equationOperator (biology)Degree (music)Hypergeometric distributionTransformation (genetics)Rational functionPure mathematicsQuadratic form (statistics)Function (biology)Algebra over a fieldCalculus (dental)CombinatoricsGeometry

Abstract

fetched live from OpenAlex

In this paper, we propose a systematic method for discovering new transformation formulas for the Gauss hypergeometric function with quadratic and rational (quadratic, cubic, and of higher degree) arguments. These new transformation formulas are obtained from known transformation formulas given in 1881 by Goursat (E. Goursat, Sur l'Équation différentielle linéaire qui admet pour intégrale la série hypergéométrique, Annales scientifique de l'É. N. S. , 2e série tome 10 [1881], 3–142). This method relies on the use of the well‐posed fractional calculus operator introduced by Tremblay (R. Tremblay, Une contribution à la théorie de la dérivée fractionnaire, Doctoral thesis, Université Laval, Québec, Canada [1974]). We illustrate the effectiveness of the method by giving several presumably new transformation formulas for the Gauss hypergeometric function.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.210
GPT teacher head0.437
Teacher spread0.227 · 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