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Record W3183915173 · doi:10.23952/jnva.4.2020.1.09

Contingent derivatives of the set-valued solution map of a noncoercive saddle point problem. A cross-fertilization between variational analysis and inverse problems

2020· article· en· W3183915173 on OpenAlexvenueno aff
Baasansuren Jadamba, Akhtar A. Khan, Miguel Sama, Christiane Tammer

Bibliographic record

VenueJournal of Nonlinear and Variational Analysis · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsnot available
FundersEuropean Regional Development FundUniversidad Nacional de Educación a DistanciaMinisterio de Ciencia, Innovación y UniversidadesAgencia Estatal de InvestigaciónNational Science Foundation
KeywordsSaddle pointSaddleInverseMathematicsApplied mathematicsSet (abstract data type)Inverse problemPoint (geometry)Human fertilizationMathematical economicsMathematical optimizationMathematical analysisComputer scienceGeometry

Abstract

fetched live from OpenAlex

We focus on the inverse problem of parameter identification in an abstract saddle point problem.Under the assumption that the saddle point problem is solvable, we study the characterizations of the first-order and the second-order contingent derivatives of the set-valued parameter-to-solution map.

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)0.003
metaresearch head score (Gemma)0.011
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.307
Teacher spread0.268 · 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
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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