{"id":"W2739127253","doi":"","title":"An Iterative Scheme for Valid Polynomial Inequality Generation in Binary Polynomial Programming","year":2010,"lang":"en","type":"article","venue":"Research portal (Tilburg University)","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; University of Waterloo","funders":"","keywords":"Semidefinite programming; Mathematics; Scheme (mathematics); Polynomial; Mathematical optimization; Convex optimization; Binary number; Regular polygon; Applied mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003258256,0.0006712247,0.00084125,0.000747052,0.0006529279,0.0009984586,0.002021169,0.0009452082,0.006039796],"category_scores_gemma":[0.008980517,0.0004836556,0.0009132709,0.000959437,0.001175825,0.001583819,0.003214498,0.002706781,0.0009606458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119608,"about_ca_system_score_gemma":0.001474063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089571,"about_ca_topic_score_gemma":0.001672899,"domain_scores_codex":[0.9978562,0.0009083014,0.0001040531,0.0002544846,0.0006581279,0.0002187147],"domain_scores_gemma":[0.9956743,0.002565505,0.0002803709,0.0008095148,0.0005207296,0.000149605],"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":[0.0003404443,0.0002578766,0.0006447468,0.0002424338,0.00005782926,0.0001763069,0.0004184076,0.3998336,0.01698404,0.3607938,0.005635965,0.2146145],"study_design_scores_gemma":[0.00003432482,0.00003380086,0.00003878582,0.00001114718,0.00000590893,0.00002702055,0.00001408033,0.9666269,0.003548896,0.02789485,0.001754563,0.000009601215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005841369,0.0000282242,0.9920276,0.00005917483,0.00001432766,0.00007486752,0.00003294062,0.0002271419,0.001694317],"genre_scores_gemma":[0.1642201,0.00004847338,0.8333256,0.00008244664,0.00001570962,0.0002292033,0.0002001822,0.0001419842,0.001736411],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006039796,"threshold_uncertainty_score":0.02020514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563709996099769,"score_gpt":0.4371438391896487,"score_spread":0.2807728395796718,"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."}}