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Record W2962878651 · doi:10.1002/jgt.22178

Packing odd<i>T</i>‐joins with at most two terminals

2017· article· en· W2962878651 on OpenAlexafffund
Ahmad Abdi, Bertrand Guenin

Bibliographic record

VenueJournal of Graph Theory · 2017
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Graph Theory Research
Canadian institutionsUniversity of Waterloo
FundersOffice of Naval Research GlobalNatural Sciences and Engineering Research Council of Canada
KeywordsCombinatoricsJoinsMathematicsBipartite graphCardinality (data modeling)ConjectureEulerian pathDisjoint setsGraphSet (abstract data type)Discrete mathematicsComputer science

Abstract

fetched live from OpenAlex

Abstract Take a graph G , an edge subset , and a set of terminals where is even. The triple is called a signed graft . A T ‐join is odd if it contains an odd number of edges from Σ. Let ν be the maximum number of edge‐disjoint odd T ‐joins. A signature is a set of the form where and is even. Let τ be the minimum cardinality a T ‐cut or a signature can achieve. Then and we say that packs if equality holds here. We prove that packs if the signed graft is Eulerian and it excludes two special nonpacking minors. Our result confirms the Cycling Conjecture for the class of clutters of odd T ‐joins with at most two terminals. Corollaries of this result include, the characterizations of weakly and evenly bipartite graphs, packing two‐commodity paths, packing T ‐joins with at most four terminals, and a new result on covering edges with cuts.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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