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Record W4312291961 · doi:10.23952/jnva.6.2022.4.07

Order-preservation properties of resolvent operators and their applications to variational inequalities

2022· article· en· W4312291961 on OpenAlexvenueno aff
Yue‐Hu Wang, Ching‐Feng Wen, Jen-Chih Yao, Congjun Zhang

Bibliographic record

VenueJournal of Nonlinear and Variational Analysis · 2022
Typearticle
Languageen
FieldComputer Science
TopicContact Mechanics and Variational Inequalities
Canadian institutionsnot available
FundersQinglan Project of Jiangsu Province of ChinaGovernment of Jiangsu ProvinceMinistry of Science and Technology, TaiwanNational Natural Science Foundation of China
KeywordsResolventVariational inequalityInequalityOrder (exchange)MathematicsResolvent formalismApplied mathematicsAlgebra over a fieldPure mathematicsCalculus (dental)Mathematical analysisFinite-rank operatorBanach spaceEconomics

Abstract

fetched live from OpenAlex

In this paper, we aim to investigate a class of new order-theoretic properties for the resolvent operators, which are called order-preservation properties.As applications, we use these orderpreservation properties and several order-theoretic fixed point theorems to prove the existence of extremal solutions for several kinds of variational inequalities arising in mechanics and economics.In contrast to many previous studies, the approaches used in this paper are mainly based on the partial order structure of the underlying spaces, and the obtained results weaken the continuity and monotonicity of the associated mappings.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0020.005
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.266
Teacher spread0.225 · 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
Published2022
Admission routes1
Has abstractyes

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