{"id":"W2533553031","doi":"10.1007/s10107-020-01484-3","title":"Outer-product-free sets for polynomial optimization and oracle-based cuts","year":2020,"lang":"en","type":"preprint","venue":"Mathematical Programming","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Polyhedron; Intersection (aeronautics); Mathematics; Cutting-plane method; Oracle; Extreme point; Relaxation (psychology); Dimension (graph theory); Product (mathematics); Combinatorics; Set (abstract data type); Convex polytope; Feasible region; Point (geometry); Regular polygon; Convex set; Mathematical optimization; Integer programming; Convex optimization; Computer science; 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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008583447,0.0006137067,0.0009924554,0.0002199304,0.0002472286,0.0004933925,0.0007952077,0.0004081666,0.0001119562],"category_scores_gemma":[0.008901063,0.0005938863,0.0002482753,0.0002745574,0.0002498278,0.0001618614,0.001455411,0.0008375447,0.00001583385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002209392,"about_ca_system_score_gemma":0.0002901324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003065318,"about_ca_topic_score_gemma":0.000001883925,"domain_scores_codex":[0.9961905,0.0001421576,0.001013424,0.001157328,0.0007649323,0.0007316787],"domain_scores_gemma":[0.9960842,0.001322641,0.0004818256,0.001269332,0.0004399475,0.0004021059],"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":[0.001533549,0.004097148,0.00006978488,0.08998559,0.001645877,0.0002564448,0.007315286,0.3241172,0.0002150485,0.08641233,0.03267076,0.451681],"study_design_scores_gemma":[0.001284772,0.0001183462,4.891064e-7,0.0003796355,0.0001465388,0.00001033553,0.00008021881,0.7647471,0.0002913468,0.2309913,0.00140021,0.0005496112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001913538,0.0001354567,0.9895875,0.004262137,0.0001910021,0.004622526,0.0001215657,0.0006281406,0.0002602537],"genre_scores_gemma":[0.002361012,0.00001307317,0.9952979,0.0001163324,0.0003484743,0.001174645,0.0002162417,0.0002367729,0.0002355646],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4511314,"threshold_uncertainty_score":0.9996513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1120649372011907,"score_gpt":0.3902809340806523,"score_spread":0.2782159968794616,"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."}}