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Record W4361016267 · doi:10.2298/fil2216521s

Subclasses of analytic functions with respect to symmetric and conjugate points connected with the q-Borel distribution

2022· article· en· W4361016267 on OpenAlexaff
H. M. Srivastava, Sheza M. El-Deeb

Bibliographic record

VenueFilomat · 2022
Typearticle
Languageen
FieldMathematics
TopicAnalytic and geometric function theory
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMathematicsConjugateComplex conjugateConjugate pointsDistribution (mathematics)Pure mathematicsFunction (biology)Regular polygonSection (typography)CombinatoricsMathematical analysisGeometry

Abstract

fetched live from OpenAlex

In this article, by making use of a q-analogue of the familiar Borel distribution, we introduce two new subclasses: S?,?,q symmetric(b, A, B) and S?,?,q conjugate(b,A, B) of starlike and convex functions in the open unit disk ? with respect to symmetric and conjugate points. We obtain some properties including the Taylor-Maclaurin coefficient estimates for functions in each of these subclasses and deduce various corollaries and consequences of the main results. We also indicate relevant connections of each of these subclasses S?,?,q symmetric(b,A, B) and S?,?,q conjugate(b,A, B) with the function classes which were investigated in several earlier works. Finally, in the concluding section, we choose to comment on the recent usages, especially in Geometric Function Theory of Complex Analysis, of the basic (or q-) calculus and also of its trivial and inconsequential (p, q)-variation involving an obviously redundant (or superfluous) parameter p.

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)0.004
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.246
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

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

Citations1
Published2022
Admission routes1
Has abstractyes

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