{"id":"W2018727518","doi":"10.1007/s10589-013-9622-z","title":"Computing the partial conjugate of convex piecewise linear-quadratic bivariate functions","year":2013,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Convex conjugate; Conjugate residual method; Derivation of the conjugate gradient method; Conjugate; Piecewise; Convex function; Applied mathematics; Conjugate gradient method; Convex analysis; Regular polygon; Mathematical analysis; Convex optimization; Mathematical optimization; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001719937,0.0007042855,0.001017615,0.0008989169,0.0003930686,0.00213303,0.000985241,0.001025278,0.005018349],"category_scores_gemma":[0.01037673,0.0005268024,0.0005259941,0.0009504039,0.001242546,0.002111471,0.001763205,0.001585046,0.0007835791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008514471,"about_ca_system_score_gemma":0.001181441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119129,"about_ca_topic_score_gemma":0.0013705,"domain_scores_codex":[0.9994344,0.00021859,0.0000241563,0.00007259253,0.0001807153,0.00006945872],"domain_scores_gemma":[0.997741,0.001341101,0.0001446632,0.0002493518,0.0003307114,0.0001932447],"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":[0.0004207658,0.0001166886,0.002232546,0.0001901229,0.00006067029,0.0001887544,0.0001764602,0.7141322,0.006856218,0.1639729,0.002757265,0.1088954],"study_design_scores_gemma":[0.000008030519,0.00004176042,0.0002096267,0.000009653631,0.000006780929,0.00003603655,0.00003481207,0.9723833,0.00254815,0.02417564,0.0005373275,0.000008915922],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09263527,0.0001194965,0.9034584,0.000211273,0.00005442388,0.00002349576,0.00008219886,0.000262435,0.003153032],"genre_scores_gemma":[0.7865429,0.00018747,0.2079923,0.0000719118,0.00004758617,0.00004491632,0.0002923572,0.0002839939,0.004536533],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005018349,"threshold_uncertainty_score":0.01678807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03456162899230268,"score_gpt":0.3328361232227529,"score_spread":0.2982744942304502,"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."}}