Bibliographic record
Abstract
Abstract For a pair of integers k, l≥0, a graph G is (k, l)‐colorable if its vertices can be partitioned into at most k independent sets and at most l cliques. The bichromatic number χb(G) of G is the least integer r such that for all k, l with k+l=r, G is (k, l)‐colorable. The concept of bichromatic numbers simultaneously generalizes the chromatic number χ(G) and the clique covering number θ(G), and is important in studying the speed of hereditary properties and edit distances of graphs. It is easy to see that for every graph G the bichromatic number χb(G) is bounded above by χ(G)+θ(G)−1. In this article, we characterize all graphs G for which the upper bound is attained, i.e., χb(G)=χ(G)+θ(G)−1. It turns out that all these graphs are cographs and in fact they are the critical graphs with respect to the (k, l)‐colorability of cographs. More specifically, we show that a cograph H is not (k, l)‐colorable if and only if H contains an induced subgraph G with χ(G)=k+1, θ(G)=l+1 and χb(G)=k+l+1. © 2010 Wiley Periodicals, Inc. J Graph Theory 65: 263–269, 2010
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".