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Record W4386404993

New families of double hypergeometric series for constants involving $\frac{1}{\pi^2}$

2020· preprint· en· W4386404993 on OpenAlexaff
John M. Campbell

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2020
Typepreprint
Languageen
FieldMathematics
TopicMathematical functions and polynomials
Canadian institutionsYork University
Fundersnot available
KeywordsPiSeries (stratigraphy)MathematicsHypergeometric distributionHypergeometric functionConstant (computer programming)CombinatoricsPure mathematicsComputer scienceGeometry
DOInot available

Abstract

fetched live from OpenAlex

We apply a Fourier--Legendre-based technique recently introduced by Campbell et al. in [J. Math. Anal. Appl. 479 (2019), 90--121] to prove new rational double hypergeometric series formulas for expressions involving $\frac{1}{\pi^2}$, especially the constant $\frac{\zeta(3)}{\pi^2}$, which is of number-theoretic interest. The techniques given in this article, applied in conjunction with Bonnet's recursion formula, give us a powerful tool for evaluating double hypergeometric sums containing products of binomial coefficients, and give us many new transformation formulas for double hypergeometric series. The double series considered in this article may be expressed as single sums involving the moments of elliptic-type integrals which have no known symbolic form, as is the case with the inner sum that we obtain by reversing the order of summation.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.059
GPT teacher head0.283
Teacher spread0.223 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes1
Has abstractyes

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