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Record W4312559246 · doi:10.23952/asvao.4.2022.3.06

R.E. Bruck, proof mining and a rate of asymptotic regularity for ergodic averages in Banach spaces

2022· article· en· W4312559246 on OpenAlexvenueno aff
Anton Freund, Ulrich Kohlenbach, Ronald E. Bruck

Bibliographic record

VenueApplied Set-Valued Analysis and Optimization · 2022
Typearticle
Languageen
FieldMathematics
TopicAdvanced Banach Space Theory
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsErgodic theoryMathematicsBanach spacePure mathematics

Abstract

fetched live from OpenAlex

We analyze a proof of Bruck to obtain an explicit rate of asymptotic regularity for Cesro means in uniformly convex Banach spaces. Our rate only depends on a norm bound and a modulus of uniform convexity. One ingredient for the proof by Bruck is a result of Pisier, which demonstrates that every uniformly convex (in fact, every uniformly nonsquare) Banach space has some Rademacher type q > 1 with a suitable constant C q . We explicitly determine q and C q , which only depend on the single value (1) of our modulus. Beyond these specific results, we summarize how work of Bruck has inspired developments in the proof mining program, which applies tools from logic to obtain results in various areas of mathematics.

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)0.008
metaresearch head score (Gemma)0.048
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 score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0020.005
Scholarly communication0.0030.009
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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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