{"id":"W3048704129","doi":"10.3233/jifs-200374","title":"An approximation algorithm for solving standard quadratic optimization problems","year":2020,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Conestoga College","funders":"","keywords":"Semidefinite programming; Algorithm; Computational complexity theory; Mathematics; Linear programming; Approximation algorithm; Heuristic; Mathematical optimization; Quadratic programming; Matrix (chemical analysis); Quadratic equation; Computer science","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":[0.001413001,0.0008823019,0.0009664504,0.0006336165,0.0005687583,0.0009940137,0.001130404,0.001157409,0.003145297],"category_scores_gemma":[0.004435452,0.0003804258,0.0007204054,0.001112681,0.0007025242,0.001217519,0.0010855,0.001994348,0.0009490268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007232006,"about_ca_system_score_gemma":0.001447538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003325189,"about_ca_topic_score_gemma":0.003022212,"domain_scores_codex":[0.9990313,0.000285555,0.00004659175,0.0001212448,0.0004351135,0.00008015537],"domain_scores_gemma":[0.998867,0.0006412803,0.00006743052,0.00009825062,0.0002926245,0.00003355595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001039051,0.00006284953,0.0003677047,0.000140061,0.0000500339,0.00006455231,0.00009109753,0.7361421,0.002134608,0.07131515,0.004132532,0.1853954],"study_design_scores_gemma":[0.000009494399,0.00001693328,0.00002645924,0.000006362456,0.000003484264,0.00001948905,0.000006570209,0.9907084,0.0002721868,0.007713127,0.001214341,0.000003206532],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001261777,0.00009643647,0.9972581,0.000050123,0.00002366162,0.00001550546,0.00001203129,0.0001034817,0.001178846],"genre_scores_gemma":[0.120092,0.0003623979,0.8755299,0.0001243283,0.00007156422,0.0002508718,0.0001769261,0.0001136776,0.003278379],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003325189,"threshold_uncertainty_score":0.01052213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08199086183557162,"score_gpt":0.3593272716802328,"score_spread":0.2773364098446612,"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."}}