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Record W1986883647 · doi:10.1090/noti1073

The Legacy of Vladimir Andreevich Steklov

2013· article· en· W1986883647 on OpenAlexaff
Nikolay Kuznetsov, Tadeusz Kulczycki, Mateusz Kwaśnicki, Alexander I. Nazarov, Sergey Poborchi, Iosif Polterovich, Bartłomiej Siudeja

Bibliographic record

VenueNotices of the American Mathematical Society · 2013
Typearticle
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsUniversité de Montréal
FundersRussian Foundation for Basic Research
KeywordsPoliticsMathematical problemMathematicsPolitical scienceLawMathematics education

Abstract

fetched live from OpenAlex

Steklov, an outstanding Russian mathematician whose 150th anniversary is celebrated this year, played an important role in the history of mathematics.Largely due to Steklov's efforts, the Russian mathematical school that gave the world such giants as N. Lobachevsky, P. Chebyshev, and A. Lyapunov, survived the revolution and continued to flourish despite political hardships.Steklov was the driving force behind the creation of the Physical-Mathematical Institute in starving Petrograd in 1921, while the civil war was still raging in the newly Soviet Russia.This institute was the predecessor of the now famous mathematical institutes in Moscow and St. Petersburg bearing Steklov's name.Steklov's own mathematical achievements, albeit less widely known, are no less remarkable than his contributions to the development of science.The Steklov eigenvalue problem, the Poincaré-Steklov operator, the Steklov function-there exist probably a dozen mathematical notions associated with Steklov.The present article highlights some of

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.004

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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 designNot applicable
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

Citations84
Published2013
Admission routes1
Has abstractyes

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