{"id":"W1994128719","doi":"10.5555/365411.365789","title":"Linear reductions of maximum matching","year":2001,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Matching (statistics); Computer science; Mathematics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006176422,0.0001715406,0.0003895005,0.0002136894,0.0001256369,0.00003115036,0.000249773,0.0001005242,0.0002713401],"category_scores_gemma":[0.00003212225,0.0001830031,0.0001702336,0.0002829224,0.00007940038,0.0001576578,0.00004268523,0.0001753009,0.0006868659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004615645,"about_ca_system_score_gemma":0.000009720596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002192178,"about_ca_topic_score_gemma":0.000002721464,"domain_scores_codex":[0.9985841,0.00003451503,0.0006487987,0.0003783947,0.00005624404,0.0002979815],"domain_scores_gemma":[0.9990312,0.00004843019,0.0003478115,0.0004573283,0.00002837198,0.00008683337],"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":[0.0001700918,0.0004879418,0.00875839,0.0001670793,0.0003256256,0.0000327335,0.003892165,0.006852321,0.00464892,0.9709771,0.001335024,0.002352602],"study_design_scores_gemma":[0.003992162,0.001797577,0.008540212,0.0005374902,0.00008698805,0.0003147957,0.002806206,0.01988195,0.01069448,0.726833,0.2218698,0.002645314],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6983019,0.0008494668,0.02593168,0.003060581,0.002892993,0.0005331677,0.0003640819,0.0002362382,0.26783],"genre_scores_gemma":[0.9918842,0.0001414849,0.001454083,0.0000795294,0.000434843,0.00001876202,0.00002385917,0.00003891585,0.005924318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2935824,"threshold_uncertainty_score":0.8828501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02791080801521452,"score_gpt":0.2495155277405985,"score_spread":0.221604719725384,"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."}}