{"id":"W2138131169","doi":"10.1007/s12532-013-0052-9","title":"Local cuts for mixed-integer programming","year":2013,"lang":"en","type":"article","venue":"Mathematical Programming Computation","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Cutting-plane method; Integer programming; Travelling salesman problem; Mathematics; Linear programming relaxation; Context (archaeology); Mathematical optimization; Relaxation (psychology); Theory of computation; Space (punctuation); Integer (computer science); Hyperplane; Point (geometry); Plane (geometry); Range (aeronautics); Linear programming; Algorithm; Computer science; Combinatorics; Geometry","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":[0.0005897023,0.0002305857,0.0003263492,0.00009238558,0.0001890703,0.0006548927,0.0004813069,0.00009537105,0.0000145623],"category_scores_gemma":[0.0002519881,0.0001856345,0.0001676983,0.000431875,0.0001128094,0.0005060687,0.0001644851,0.0001617466,0.0002396748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005447877,"about_ca_system_score_gemma":0.00002979789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000012017,"about_ca_topic_score_gemma":3.276001e-7,"domain_scores_codex":[0.9979713,0.00009957097,0.0004988388,0.0004927666,0.0003640567,0.0005734657],"domain_scores_gemma":[0.9983757,0.0007143529,0.0001489815,0.0002858748,0.0002559784,0.0002191368],"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":[0.000001540677,0.0001906729,0.000004523333,0.0001139705,0.00001514411,0.000001731536,0.0001979607,0.0001611513,0.00002788012,0.06263632,0.0003096269,0.9363395],"study_design_scores_gemma":[0.0002469706,0.0002122143,0.00002947314,0.0000507851,0.00000995716,0.00001619358,0.00008217083,0.7313723,0.0002202682,0.2621396,0.005400869,0.0002191432],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004648862,0.000032576,0.9958323,0.001132006,0.0002766699,0.001439667,4.402967e-7,0.0005761315,0.0002453253],"genre_scores_gemma":[0.1208558,3.157134e-7,0.8782083,0.000122767,0.00007963993,0.0006061547,0.000005802419,0.00002361603,0.00009749244],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9361203,"threshold_uncertainty_score":0.7569954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02548378838351857,"score_gpt":0.3091325737675542,"score_spread":0.2836487853840356,"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."}}