{"id":"W2745815247","doi":"10.1109/cvpr.2017.642","title":"Adaptive and Move Making Auxiliary Cuts for Binary Pairwise Energies","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Submodular set function; Pairwise comparison; Computer science; Binary number; Context (archaeology); State (computer science); Extension (predicate logic); Algorithm; Function (biology); Theoretical computer science; Mathematical optimization; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003245684,0.002298969,0.002382214,0.001610765,0.0007103748,0.001511416,0.003956157,0.002668296,0.006488288],"category_scores_gemma":[0.01122546,0.0008790604,0.001680643,0.001696174,0.001462861,0.003177617,0.003270019,0.003469945,0.001114561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417897,"about_ca_system_score_gemma":0.001343979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001622827,"about_ca_topic_score_gemma":0.002855788,"domain_scores_codex":[0.997831,0.0009045916,0.00008481444,0.0004062198,0.000559675,0.0002136173],"domain_scores_gemma":[0.995433,0.002905517,0.0003967891,0.0006242099,0.0004311626,0.0002094269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003611346,0.0002444777,0.0008895931,0.0002872708,0.0001288784,0.0001456865,0.0001941343,0.7230511,0.0056017,0.06861737,0.005947414,0.1945312],"study_design_scores_gemma":[0.0000299834,0.00009760898,0.0001287355,0.00002080618,0.00001543388,0.00005726519,0.00002775131,0.9755595,0.001240079,0.02166764,0.001144081,0.00001110998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01539514,0.0002696973,0.9811766,0.0001468057,0.00003576258,0.0001169492,0.0001031336,0.0004550329,0.00230095],"genre_scores_gemma":[0.3163498,0.0002437112,0.6773049,0.0003189063,0.00009538329,0.0004880995,0.0006460912,0.0005171273,0.004035933],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006488288,"threshold_uncertainty_score":0.02170551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04338587632187273,"score_gpt":0.3100333385755564,"score_spread":0.2666474622536837,"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."}}