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Record W4403730190 · doi:10.23952/jnva.8.2024.6.08

Path connectedness of solution sets for partially ordered set optimization problems

2024· article· en· W4403730190 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Nonlinear and Variational Analysis · 2024
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Variational Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSocial connectednessPath (computing)Set (abstract data type)MathematicsMathematical optimizationTopology (electrical circuits)Computer scienceCombinatoricsPsychologySocial psychology

Abstract

fetched live from OpenAlex

The aim of this paper is to study the path connectedness of the minimal and weak minimal solution sets for set optimization problems equipped with partial set order relations defined on the family of bounded sets by means of Minkowski difference.We propose some new notions of generalized convexity for set-valued maps and a lower level map.Further, by investigating several properties of this level map, we study path connectedness of the solution sets for set optimization problems with respect to partial order relations.Finally, we give an application of the derived results to Nash equilibrium games with vector-valued maps under uncertainty.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.408
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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