{"id":"W4403324132","doi":"10.48550/arxiv.2410.05240","title":"Vizing's Theorem in Near-Linear Time","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; European Commission; Simons Institute for the Theory of Computing, University of California Berkeley; United States-Israel Binational Science Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003224145,0.002592228,0.002019521,0.001665627,0.002228951,0.004946169,0.005555873,0.002635578,0.02107669],"category_scores_gemma":[0.0161407,0.001487526,0.004155525,0.003525234,0.002968213,0.0109678,0.006541957,0.005472066,0.009868299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004839175,"about_ca_system_score_gemma":0.005569671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767682,"about_ca_topic_score_gemma":0.005283476,"domain_scores_codex":[0.993066,0.001168516,0.0005400743,0.002682733,0.001682168,0.0008604458],"domain_scores_gemma":[0.9862193,0.006385364,0.0005907707,0.005684408,0.0008501372,0.0002699679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001741344,0.0004026051,0.002682897,0.001567157,0.0004398498,0.0003236726,0.0005331975,0.0631653,0.01894195,0.4237257,0.09257269,0.3939037],"study_design_scores_gemma":[0.0004044875,0.0001693163,0.0008399492,0.00008526832,0.0002179973,0.0003945291,0.0001550074,0.1652543,0.01053427,0.7775196,0.04432857,0.00009666524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02831843,0.001855607,0.8927828,0.00789229,0.0009180763,0.0007914539,0.002351659,0.01903738,0.0460523],"genre_scores_gemma":[0.3376034,0.001834348,0.6172154,0.00373781,0.000812041,0.001125047,0.005216702,0.00298279,0.0294725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02107669,"threshold_uncertainty_score":0.07050854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05011162665424287,"score_gpt":0.1885628265528209,"score_spread":0.138451199898578,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}