Why this work is in the frame
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Bibliographic record
Abstract
Given a graph G = (V, E), an odd cycle cover is a subset of the vertices whose removal makes the graph bipartite, that is, it meets all odd cycles in G. A packing in G is a collection of vertex disjoint odd cycles. This thesis addresses algorithmic and structural problems concerning odd cycle covers and packings. In particular, we consider the two NP-hard problems of finding a maximum packing and a minimum covering. In 1994 Brass [53] conjectured that tau, the minimum size of an odd cycle cover, is at most twice nu, the maximum size of a packing. The conjecture is known to be false in general [11, 41]. We prove here that tau < 10nu for planar graphs. Our structural results leads to the first constant approximation algorithm for the packing problem. The covering problem was shown to be tractable for graphs of constant sized solutions [42]. We give a linear time algorithm for the covering problem restricted to the case where the graphs have constant sized solutions and are planar.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it