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Record W2040426893 · doi:10.1556/sscmath.42.2005.3.3

Partitioning a graph into vertex-disjoint paths

2005· article· en· W2040426893 on OpenAlex
Jianping Li, George Steiner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudia Scientiarum Mathematicarum Hungarica · 2005
Typearticle
Languageen
FieldMathematics
TopicGraph theory and applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCombinatoricsMathematicsDisjoint setsVertex (graph theory)GraphDiscrete mathematicsInteger (computer science)Computer science

Abstract

fetched live from OpenAlex

Let G =( V , E ) be a simple graph of order n . We consider the problem of partitioning G into vertex-disjoint paths. We obtain the following new results: (i) For any positive integer k , if d G ( x )+ d G ( y ) = n - k -1 for every pair x , y of nonadjacent vertices in G , then G can be partitioned into k vertex-disjoint paths, unless G belongs to certain classes of extremal graphs which we characterize; (ii) For the case k =2, we strengthen our result by showing that for any two positive integers p 1 and p 2 satisfying n = p 1 + p 2 ,if d G ( x )+ d G ( y ) = n -3 for every pair x, y of nonadjacent vertices in G and G does not belong to classes of exceptional graphs we define, then G can be partitioned into two vertex-disjoint paths P 1 and P 2 of order p 1 and p 2 , respectively. These results are generalizations of some classical results of Dirac and Ore, and also lead to new sufficient conditions for the existence of a Hamilton path in a graph.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.304
Teacher spread0.276 · 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