{"id":"W2130895332","doi":"10.1007/s10107-008-0258-1","title":"A retrospective trust-region method for unconstrained optimization","year":2008,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Trust region; Mathematics; Convergence (economics); Current (fluid); Mathematical optimization; Function (biology); Order (exchange); Numerical analysis; Applied mathematics; Value (mathematics); RADIUS; Computer science; Statistics; Mathematical analysis","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":[0.003252304,0.00119219,0.001641081,0.0006959974,0.0004826451,0.001478793,0.002389274,0.001632592,0.005608654],"category_scores_gemma":[0.01263452,0.001038541,0.001226943,0.0008244115,0.001175,0.00209156,0.002254936,0.002448357,0.001954579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005738261,"about_ca_system_score_gemma":0.001472209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003016618,"about_ca_topic_score_gemma":0.001958107,"domain_scores_codex":[0.9989061,0.0004911211,0.00005627442,0.0001384528,0.0003565619,0.00005147128],"domain_scores_gemma":[0.9954397,0.002747104,0.0003049431,0.0004755897,0.0008638913,0.0001687453],"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":[0.0004706171,0.00009997346,0.0006316547,0.0005042065,0.0001279248,0.0001945185,0.000174898,0.757632,0.007391997,0.1051223,0.00587133,0.1217785],"study_design_scores_gemma":[0.00001122891,0.00004009821,0.00003320396,0.00001380419,0.00001085507,0.00003196293,0.000004373201,0.9926231,0.0007484191,0.004541524,0.001930953,0.00001058891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008037454,0.0001027248,0.9983395,0.00002974271,0.00003387365,0.00001553374,0.00001992125,0.00008343339,0.0005715152],"genre_scores_gemma":[0.08734763,0.0004708489,0.9051334,0.00008856976,0.0001481842,0.000236202,0.0002181784,0.0004773476,0.005879626],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005608654,"threshold_uncertainty_score":0.01876277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09041040462034387,"score_gpt":0.3916623311692999,"score_spread":0.3012519265489561,"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."}}