MétaCan
Menu
Back to cohort
Record W2953254115 · doi:10.1002/rsa.20266

On the girth of random Cayley graphs

2009· article· en· W2953254115 on OpenAlexaff
Alex Gamburd, Shlomo Hoory, Mehrdad Shahshahani, Aner Shalev, Bálint Virág

Bibliographic record

VenueRandom Structures and Algorithms · 2009
Typearticle
Languageen
FieldMathematics
TopicFinite Group Theory Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCayley graphMathematicsGirth (graph theory)CombinatoricsDiscrete mathematicsOdd graphRandom graphAlgebraic numberChordal graphGraph1-planar graph

Abstract

fetched live from OpenAlex

Abstract We prove that random d‐regular Cayley graphs of the symmetric group asymptotically almost surely have girth at least (logd‐1|G|)1/2/2 and that random d‐regular Cayley graphs of simple algebraic groups over 𝔽q asymptotically almost surely have girth at least log d‐1|G|/dim(G). For the symmetric p‐groups the girth is between loglog |G| and (log |G|)α with α < 1. Several conjectures and open questions are presented. © 2009 Wiley Periodicals, Inc. Random Struct. Alg., 2009

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)0.004
metaresearch head score (Gemma)0.041
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0020.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.304
Teacher spread0.274 · 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

Citations28
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueRandom Structures and AlgorithmsSame topicFinite Group Theory ResearchFrench-language works237,207