MétaCan
Menu
Back to cohort
Record W2730795281 · doi:10.1051/cocv/2017069

On two functionals involving the maximum of the torsion function

2017· article· en· W2730795281 on OpenAlexaff
Antoine Henrot, Ilaria Lucardesi, G. A. Philippin

Bibliographic record

VenueESAIM Control Optimisation and Calculus of Variations · 2017
Typearticle
Languageen
FieldMathematics
TopicNonlinear Partial Differential Equations
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTorsion (gastropod)MathematicsBounded functionRegular polygonPure mathematicsOpen setUpper and lower boundsEigenvalues and eigenvectorsCombinatoricsMathematical analysisGeometryPhysics

Abstract

fetched live from OpenAlex

In this paper we investigate upper and lower bounds of two shape functionals involving the maximum of the torsion function. More precisely, we considerT(Ω)∕(M(Ω)|Ω|) andM(Ω)λ1(Ω), whereΩis a bounded open set of ℝdwith finite Lebesgue measure |Ω|,M(Ω) denotes the maximum of the torsion function,T(Ω) the torsion, andλ1(Ω) the first Dirichlet eigenvalue. Particular attention is devoted to the subclass of convex sets.

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)0.034
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 score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.034
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0020.007
Scholarly communication0.0040.009
Open science0.0030.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.039
GPT teacher head0.312
Teacher spread0.273 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueESAIM Control Optimisation and Calculus of VariationsSame topicNonlinear Partial Differential EquationsFrench-language works237,207