{"id":"W4382934680","doi":"10.1016/j.orl.2023.06.004","title":"Continuous cutting plane algorithms in integer programming","year":2023,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Subadditivity; Cutting-plane method; Integer programming; Mathematical optimization; Mathematics; Integer (computer science); Linear programming; Algorithm; Optimization problem; Theory of computation; Branch and cut; Computer science; Combinatorics","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":[0.0008158858,0.00008151514,0.00009431649,0.0005360754,0.0001596183,0.0002430783,0.0001371472,0.00004559444,0.00008036196],"category_scores_gemma":[0.0001186561,0.00008362594,0.00001962586,0.001275986,0.00004854652,0.0001695319,0.00003868918,0.0004032662,0.0003939375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007734278,"about_ca_system_score_gemma":0.00001973531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001261978,"about_ca_topic_score_gemma":0.000158722,"domain_scores_codex":[0.998865,0.00008652182,0.0001883408,0.0001547755,0.0002606299,0.0004447258],"domain_scores_gemma":[0.9996336,0.00009113941,0.000003575708,0.0001506101,0.00006076273,0.00006028593],"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":[0.000001168304,0.00001000812,0.0006038907,0.000024297,0.00000953883,0.00003556236,0.001186314,0.9712855,0.005486032,0.0001661816,0.008836349,0.01235513],"study_design_scores_gemma":[0.0002674193,0.00001668493,0.0003462085,0.0000690311,0.000001015072,0.000004604554,0.000481918,0.9685299,0.0009225723,0.000005975194,0.02920946,0.0001452046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9068831,0.0002013982,0.05822726,0.01729109,0.001106517,0.002224524,0.00003635935,0.002652436,0.01137731],"genre_scores_gemma":[0.984449,0.0001070548,0.013094,0.0002239334,0.0001721604,0.0003280102,0.000223368,0.00006708438,0.0013354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07756589,"threshold_uncertainty_score":0.5063401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05034676274351741,"score_gpt":0.3328587710717831,"score_spread":0.2825120083282657,"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."}}