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Record W4288112285 · doi:10.48550/arxiv.1909.04023

Noncommutative analogues of a cancellation theorem of Abhyankar, Eakin,\n and Heinzer

2019· preprint· en· W4288112285 on OpenAlexfundno aff
Jason P. Bell, Maryam Hamıdızadeh, Hongdi Huang, Helbert Venegas

Bibliographic record

VenuearXiv (Cornell University) · 2019
Typepreprint
Languageen
FieldMathematics
TopicRings, Modules, and Algebras
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMathematicsNoncommutative geometryCommutative propertyPolynomial ringCounterexampleDiscrete mathematicsPure mathematicsAlgebra over a fieldPolynomialMathematical analysis

Abstract

fetched live from OpenAlex

Let $k$ be a field and let $A$ be a finitely generated $k$-algebra. The\nalgebra $A$ is said to be cancellative if whenever $B$ is another $k$-algebra\nwith the property that $A[x]\\cong B[x]$ then we necessarily have $A\\cong B$. An\nimportant result of Abhyankar, Eakin, and Heinzer shows that if $A$ is a\nfinitely generated commutative integral domain of Krull dimension one then it\nis cancellative. We consider the question of cancellation for finitely\ngenerated not-necessarily-commutative domains of Gelfand-Kirillov dimension\none, and show that such algebras are necessarily cancellative when the\ncharacteristic of the base field is zero. In particular, this recovers the\ncancellation result of Abhyankar, Eakin, and Heinzer in characteristic zero\nwhen one restricts to the commutative case. We also provide examples that show\naffine domains of Gelfand-Kirillov dimension one need not be cancellative when\nthe base field has positive characteristic, giving a counterexample to a\nconjecture of Tang, the fourth-named author, and Zhang. In addition, we prove a\nskew analogue of the result of Abhyankar-Eakin-Heinzer, in which one works with\nskew polynomial extensions as opposed to ordinary polynomial rings.\n

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.085
GPT teacher head0.225
Teacher spread0.140 · 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.

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
Published2019
Admission routes1
Has abstractyes

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