{"id":"W2513208540","doi":"10.1155/2016/5017369","title":"Certificates of Optimality for Mixed Integer Linear Programming Using Generalized Subadditive Generator Functions","year":2016,"lang":"en","type":"article","venue":"Advances in Operations Research","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Subadditivity; Knapsack problem; Integer (computer science); Integer programming; Mathematics; Generator (circuit theory); Duality (order theory); Linear programming; Class (philosophy); Discrete mathematics; Mathematical optimization; Combinatorics; Computer science; Power (physics)","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":[0.001998806,0.0001871858,0.0003545076,0.0006007418,0.0004579392,0.00006002654,0.0003632692,0.000122885,0.0002659967],"category_scores_gemma":[0.006832878,0.0001392906,0.00009617006,0.0012598,0.0005705715,0.0009791869,0.0001591824,0.0002847646,0.00001319882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003650422,"about_ca_system_score_gemma":0.0003324631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000510409,"about_ca_topic_score_gemma":0.0004793409,"domain_scores_codex":[0.9968393,0.0005561779,0.0007453755,0.0005328814,0.0006669833,0.0006592539],"domain_scores_gemma":[0.9947159,0.002073204,0.00007476595,0.0005342105,0.002469374,0.000132566],"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":[0.001082346,0.002618263,0.001682239,0.0006403267,0.000240508,0.00001506517,0.001729578,0.5364303,0.1397518,0.1471335,0.001976683,0.1666994],"study_design_scores_gemma":[0.003701019,0.0004616207,0.00003484739,0.0003782269,0.00002738223,0.000009682259,0.00187914,0.7923366,0.1543602,0.01703438,0.02914264,0.0006343111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03177328,0.0005157312,0.9644915,0.0005897496,0.0001468721,0.001918203,0.0003967445,0.00005602443,0.0001118214],"genre_scores_gemma":[0.08545673,0.0005828209,0.9098945,0.000008418979,0.0001907648,0.001468486,0.0000932605,0.00007220008,0.002232789],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2559063,"threshold_uncertainty_score":0.8180086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2457099591087016,"score_gpt":0.5069657763647945,"score_spread":0.2612558172560928,"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."}}