{"id":"W2165352378","doi":"10.5555/1070432.1070490","title":"An O(VE) algorithm for ear decompositions of matching-covered graphs","year":2005,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Partition (number theory); Matching (statistics); Algorithm; Running time; Computer science; Mathematics; Blossom algorithm; Combinatorics; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006241282,0.0003525968,0.0004108291,0.0004693272,0.0003646059,0.0001713141,0.00184616,0.000131075,0.00002369286],"category_scores_gemma":[0.00001543849,0.0003331254,0.0003142911,0.00074059,0.0002011466,0.001304318,0.0002106598,0.0002742965,0.00004720195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008910955,"about_ca_system_score_gemma":0.00008929524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002382635,"about_ca_topic_score_gemma":0.000006466801,"domain_scores_codex":[0.9969476,0.0001943231,0.0005353418,0.0008769845,0.0006815972,0.0007641225],"domain_scores_gemma":[0.9974373,0.0003203273,0.0002021868,0.001434033,0.000259485,0.0003466652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001793583,0.001270175,0.00005247989,0.00007353262,0.0002418938,0.00002206625,0.002889137,0.01310971,0.1016569,0.4586363,0.000632007,0.4212364],"study_design_scores_gemma":[0.002604389,0.00265884,0.0003332872,0.0001054554,0.00003911277,0.00004660678,0.0002295245,0.6590117,0.1259669,0.2051498,0.002849882,0.001004496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008726283,0.00010405,0.9871163,0.001136521,0.00028748,0.000813236,0.0002929877,0.0002727922,0.001250363],"genre_scores_gemma":[0.1917589,0.00006701821,0.806882,0.0003648673,0.0002360964,0.0002096173,0.00008342561,0.00006887796,0.0003291625],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.645902,"threshold_uncertainty_score":0.9999121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323844639757141,"score_gpt":0.3080781382825517,"score_spread":0.2948396918849802,"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."}}