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Record W2965285632 · doi:10.4213/rm9892

Дискретизация интегральной нормы и близкие задачи

2019· article· ru· W2965285632 on OpenAlexafffund
Chang‐Feng Dai, Andriy Prymak, Vladimir Temlyakov, Sergei Yur'evich Tikhonov

Bibliographic record

VenueУспехи математических наук · 2019
Typearticle
Languageru
FieldMathematics
TopicMathematical Approximation and Integration
Canadian institutionsUniversity of ManitobaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia e InnovaciónMinistry of Education and Science of the Russian FederationGeneralitat de Catalunya
KeywordsGeography

Abstract

fetched live from OpenAlex

В статье обсуждается задача о замене интегральной нормы по заданной вероятностной мере соответствующей интегральной нормой по дискретной мере. Указанная задача изучается для элементов конечномерных пространств. Также рассматривается дискретизация равномерной нормы для функций из заданного конечномерного подпространства непрерывных функций. Особое внимание уделено случаю многомерных тригонометрических полиномов со спектрами из конечных множеств заданной мощности. Мы приводим как новые результаты, так и обзор известных результатов. Библиография: 47 названий.

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)0.002
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 score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.007
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.005

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 head0.031
GPT teacher head0.298
Teacher spread0.266 · 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

Citations22
Published2019
Admission routes2
Has abstractyes

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