{"id":"W2788376296","doi":"10.3846/mma.2018.001","title":"An Arc Search Interior-Point Algorithm for Monotone Linear Complementarity Problems over Symmetric Cones","year":2018,"lang":"en","type":"article","venue":"Mathematical Modelling and Analysis","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interior point method; Mathematics; Monotone polygon; Arc (geometry); Complementarity (molecular biology); Linear complementarity problem; Ellipse; Ellipsoid; Algorithm; Convergence (economics); Point (geometry); Path (computing); Search algorithm; Mathematical optimization; Combinatorics; Geometry; Computer science; Nonlinear system","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":[0.001237738,0.0002701088,0.0007335093,0.0006503245,0.0003458947,0.0001550654,0.0002720485,0.0001067781,0.0004477155],"category_scores_gemma":[0.0001615102,0.0002278349,0.000223095,0.001234066,0.0002837204,0.0002227034,0.0001332147,0.0002197146,0.00001785989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006806398,"about_ca_system_score_gemma":0.00002619652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000530712,"about_ca_topic_score_gemma":0.00001469865,"domain_scores_codex":[0.9975298,0.0001196839,0.0007019416,0.0005802111,0.0005414746,0.0005268875],"domain_scores_gemma":[0.9977418,0.0007706255,0.0001324404,0.0005269527,0.0005368884,0.0002913439],"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":[0.0004072014,0.007192359,0.001900376,0.004270081,0.01262883,0.00002952436,0.02271459,0.4307659,0.001356954,0.3634646,0.0003920789,0.1548776],"study_design_scores_gemma":[0.0004757534,0.0002070876,0.000005115639,0.00003933741,0.0004101427,0.000002289436,0.0002358823,0.822597,0.0005093638,0.1752611,0.00003514563,0.0002217305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02581999,0.00003263907,0.9730195,0.0001115418,0.00001598062,0.0006481244,0.00009043243,0.00011179,0.0001499832],"genre_scores_gemma":[0.1602702,0.0000337962,0.8390499,0.00004236449,0.0001170845,0.00009195909,0.00006667045,0.00004797963,0.0002800295],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3918312,"threshold_uncertainty_score":0.9290839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097320074911878,"score_gpt":0.3968934424576526,"score_spread":0.2871614349664648,"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."}}