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Record W2084570563 · doi:10.1093/imrn/rnq172

The Direct Sum Map on Grassmannians and Jeu de Taquin for Increasing Tableaux

2010· article· en· W2084570563 on OpenAlexaff
Hugh Thomas, Alexander Yong

Bibliographic record

VenueInternational Mathematics Research Notices · 2010
Typearticle
Languageen
FieldMathematics
TopicAdvanced Combinatorial Mathematics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMathematicsStructure constantsSchubert calculusPullbackProduct (mathematics)Boundary (topology)Identity (music)RectificationIdeal (ethics)Pure mathematicsCombinatoricsMathematical analysisGeometryGrassmannianPhysicsLawPower (physics)

Abstract

fetched live from OpenAlex

The direct sum map on Grassmannians induces a K-theory pullback that defines the splitting coefficients. We geometrically explain an identity from Buch [“Grothendieck classes of quiver varieties.” Duke Mathematical Journal 115, no. 1 (2002): 75–103] between the splitting coefficients and the Schubert structure constants for products of Schubert structure sheaves. This is related to the topic of product and splitting coefficients for Schubert boundary ideal sheaves. Our main results extend jeu de taquin for increasing tableaux [Thomas and Yong. “A jeu de taquin theory for increasing tableaux, with applications to K-theoretic Schubert calculus.” Algebra and Number Theory Journal 3, no. 2 (2009): 121–48] by proving transparent analogues of Schützenberger’s [“La Correspondance de Robinson.” In Combinatoire et Représentation du Groupe Symétrique (Strasbourg, 1976), edited by D. Foata, 59–113. Lecture Notes in Mathematics 579. Berlin: Springer, 1977] fundamental theorems on well definedness of rectification. We then establish that jeu de taquin gives rules for each of these four kinds of coefficients.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.005
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0010.003
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 head0.109
GPT teacher head0.454
Teacher spread0.345 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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Same venueInternational Mathematics Research NoticesSame topicAdvanced Combinatorial MathematicsFrench-language works237,207