MétaCan
Menu
Back to cohort
Record W3123395265 · doi:10.1090/tran/8373

Corrigenda to “Codomain rigidity of the Dirichlet to Neumann operator for the Riemannian wave equation”

2021· article· en· W3123395265 on OpenAlexafffund
Tristan Milne, Abdol-Reza Mansouri

Bibliographic record

VenueTransactions of the American Mathematical Society · 2021
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Mathematical Modeling in Engineering
Canadian institutionsQueen's UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMathematicsDirichlet distributionMonotonic functionConvex functionLemma (botany)Operator (biology)Regular polygonLogarithmically convex functionRigidity (electromagnetism)Quadratic equationFunction (biology)Pure mathematicsMathematical analysisCombinatoricsSubderivativeConvex optimizationBoundary value problemGeometry

Abstract

fetched live from OpenAlex

The proof of Lemma 4.4 in our article, which appeared in Trans. Amer. Math. Soc. 371 (2019), 8781–8810, contains a flaw. In proving the existence of a minimizer of the map A ↦ I ϵ [ A ] \mathbf {A} \mapsto I_\epsilon [\mathbf {A}] defined therein, we stated that this map is a convex function of A \mathbf {A} . This is incorrect, as I ϵ I_\epsilon is a composition of two convex functions, a quadratic form and an absolute value, and since the absolute value function is not monotonic, there is no guarantee that the resulting functional is convex. This short article corrects this flaw by showing that there is a continuous convex functional J ϵ J_\epsilon such that I ϵ [ A ] = J ϵ [ A 2 ] I_\epsilon [\mathbf {A}] = J_\epsilon [\mathbf {A}^2] , and then employing weak lower semi-continuity of J ϵ J_\epsilon to demonstrate the existence of a minimizer of I ϵ I_\epsilon .

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.133
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1330.033

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 head0.034
GPT teacher head0.277
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the American Mathematical SocietySame topicAdvanced Mathematical Modeling in EngineeringFrench-language works237,207