{"id":"W3212784844","doi":"10.1007/s10589-022-00364-0","title":"Malitsky-Tam forward-reflected-backward splitting method for nonconvex minimization problems","year":2022,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Monotone polygon; Regularization (linguistics); Stationary point; Minification; Property (philosophy); Quadratic equation; Applied mathematics; Rate of convergence; Convergence (economics); Mathematical optimization; Mathematical analysis; Computer science; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005228565,0.0002097893,0.0002416106,0.0003542307,0.001418424,0.0002741908,0.0004772712,0.00005941599,0.000183557],"category_scores_gemma":[0.00005637888,0.0002395851,0.0001207523,0.001546495,0.00003563526,0.0004536021,0.0002632781,0.0001317078,0.000008289292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116113,"about_ca_system_score_gemma":0.0001946184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007538171,"about_ca_topic_score_gemma":0.000001391442,"domain_scores_codex":[0.9978499,0.0001692541,0.0005948857,0.000683255,0.0004531609,0.000249479],"domain_scores_gemma":[0.9980704,0.0004714885,0.0003882301,0.0002933905,0.0006326162,0.0001439022],"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":[0.00000442957,0.00009676876,0.00005655328,0.00001775323,0.00003652662,9.694529e-8,0.0001871392,0.7620299,0.000009574956,0.2320284,0.0005697407,0.004963119],"study_design_scores_gemma":[0.0007187959,0.00005328545,0.0001417851,0.000003792579,0.00004107691,0.00001583555,0.0000719962,0.9517422,0.00001224242,0.01927316,0.02766252,0.0002633382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001178701,0.00009182021,0.992652,0.004840581,0.00008911147,0.001156504,0.0001034464,0.0002663555,0.0007883962],"genre_scores_gemma":[0.01253668,0.00002387202,0.9806944,0.001913449,0.0001123619,0.002262515,0.001702466,0.00002972174,0.0007245069],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2127552,"threshold_uncertainty_score":0.9998816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663454718498633,"score_gpt":0.2905574431592843,"score_spread":0.273922895974298,"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."}}