{"id":"W2921296408","doi":"10.48550/arxiv.1903.05304","title":"On the depth of cutting planes","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polyhedron; Intersection (aeronautics); Cutting-plane method; Simplex; Mathematics; Plane (geometry); Geometry; Parametric statistics; Combinatorics; Algorithm; Integer programming; Engineering","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":[0.0001217172,0.0001893058,0.0002179775,0.0001186342,0.00003199882,0.00001386408,0.0004830897,0.0002082684,0.00005132275],"category_scores_gemma":[0.00001727815,0.0001661238,0.0001188809,0.0001265255,0.00004166153,0.00003772727,0.0001714175,0.0004451422,0.00005930947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000587865,"about_ca_system_score_gemma":0.00002046967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003336924,"about_ca_topic_score_gemma":0.00000596378,"domain_scores_codex":[0.9993944,0.0000376938,0.0001162639,0.0002431339,0.00004697365,0.0001615141],"domain_scores_gemma":[0.9991211,0.0001816079,0.00007358534,0.0005613139,0.00003119648,0.00003123795],"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":[0.00001995836,0.00002792051,0.002600032,0.0003538246,0.0001689907,0.00005286976,0.000178867,0.8879606,0.0005440179,0.1039171,0.003620688,0.0005551194],"study_design_scores_gemma":[0.0004956455,0.0001685144,0.002289186,0.001098386,0.0002448389,0.000006109923,0.0003714591,0.8764555,0.0315614,0.08426123,0.001808979,0.001238718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.83785,0.0001004659,0.09405003,0.00001518827,0.0003874888,0.0004204648,0.00003520148,0.0006343338,0.06650678],"genre_scores_gemma":[0.9991919,0.0001623377,0.00009478458,0.00002119785,0.0000326272,6.078979e-7,0.00000957891,0.00002769332,0.0004592922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1613418,"threshold_uncertainty_score":0.6774333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0607409193743733,"score_gpt":0.1593384722370432,"score_spread":0.09859755286266993,"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."}}