{"id":"W1980738047","doi":"10.2168/lmcs-8(3:5)2012","title":"Formalizing Randomized Matching Algorithms","year":2012,"lang":"en","type":"article","venue":"Logical Methods in Computer Science","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bipartite graph; Correctness; 3-dimensional matching; Blossom algorithm; Lemma (botany); Perfect graph theorem; Algorithm; Matching (statistics); Factor-critical graph; Computer science; Discrete mathematics; Mathematics; Theoretical computer science; Graph; Voltage graph; Line graph","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.01829254,0.0002725512,0.0006553273,0.0004953123,0.0004371445,0.0005033664,0.003143701,0.00009293151,0.00001921639],"category_scores_gemma":[0.0004171688,0.0002065072,0.0002110327,0.002655964,0.0009771669,0.00265409,0.002335497,0.0004703832,0.00002305034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009342413,"about_ca_system_score_gemma":0.00006770107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000327401,"about_ca_topic_score_gemma":6.898869e-7,"domain_scores_codex":[0.9954978,0.001139015,0.000653562,0.0007605749,0.0007125865,0.001236458],"domain_scores_gemma":[0.9962791,0.002272764,0.0001668219,0.0008216684,0.00009129081,0.0003683401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005002666,0.000107211,0.0001413629,0.000007049447,0.000004411426,0.000007840616,0.001360024,0.0004149135,0.0002819039,0.3800394,0.00000568315,0.6175802],"study_design_scores_gemma":[0.005721387,0.00004043995,0.001580157,0.00003602455,0.000003400102,0.00009050344,0.00001290678,0.7175606,0.001348291,0.2729299,0.0003267462,0.0003496291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002689107,0.0003446024,0.9911976,0.000331765,0.003179881,0.0003187245,3.723139e-7,0.0002657817,0.001672176],"genre_scores_gemma":[0.07836675,0.00001835702,0.9203317,0.0009400456,0.0002941961,0.00003408794,2.467552e-7,0.000006384911,0.000008228095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7171457,"threshold_uncertainty_score":0.8421118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08537728207017845,"score_gpt":0.3975713719226918,"score_spread":0.3121940898525133,"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."}}