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Record W4413838596 · doi:10.24908/iqurcp19826

The Lattice property of biclosed sets for infinite root systems

2025· article· en· W4413838596 on OpenAlexaffvenue
Jeremy Hare-Chang, Yixin Ma, Ivan Dimitrov, Charles Paquette, David L. Wehlau

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2025
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Algebra and Logic
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsRoot (linguistics)Property (philosophy)Lattice (music)MathematicsPure mathematicsPhysicsPhilosophyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

A root system is a finite collection of vectors in Euclidean space satisfying certain symmetry conditions. Work by Killing and Cartan in the late 19th century showed that these come in seven families, and uses this fact to classify the semisimple Lie algebras. Root systems play an important role in many fields, including the representation theory of algebras, algebraic geometry, and particle physics. Relaxing the finiteness assumption in the definition of root system leads to the more general notion of a Kac–Moody root system. In the finite setting, root systems can be studied via their inversion sets, which are objects carrying geometric information. This does not carry over to Kac-Moody root systems. However, the inversion sets are completely characterised by two closure properties, making them so-called biclosed sets. Following work of Barkley and Speyer, we investigate biclosed sets as a generalization of inversion sets to infinite root systems, especially a family called the hyperbolic root systems. Their result that these sets form a lattice in affine type is found not to hold when the sets are allowed to contain imaginary roots, and the related “2-out-of-3 rule” also fails without this restriction. We explored distinctions between two different notions of closure used to define a biclosed set. Several interesting questions arose from these areas.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.940
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.107
GPT teacher head0.383
Teacher spread0.275 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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