{"id":"W4403191597","doi":"10.1007/s10589-024-00604-5","title":"The indefinite proximal gradient method","year":2024,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Proximal Gradient Methods; Applied mathematics; Mathematical optimization; Geometry; Regular polygon; Convex function","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":[],"consensus_categories":[],"category_scores_codex":[0.0004827352,0.0000979016,0.00008901109,0.00006278897,0.0003901503,0.000199486,0.0001086711,0.00004051261,0.00003516681],"category_scores_gemma":[0.0001185289,0.0000710904,0.00004054883,0.0004238528,0.0001032272,0.00008068524,0.00005358258,0.0001293536,0.00002245818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003177607,"about_ca_system_score_gemma":0.00004793386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001073306,"about_ca_topic_score_gemma":3.0421e-7,"domain_scores_codex":[0.9991133,0.00009662582,0.0002597064,0.0002348636,0.0001745781,0.0001209636],"domain_scores_gemma":[0.997274,0.002361583,0.0000585284,0.0001354929,0.0001072915,0.00006314338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001590507,0.0000209685,0.000005802116,0.00002818296,0.0000213217,2.272786e-7,0.0000861651,0.1316292,0.000003589267,0.8408008,0.00088822,0.02651388],"study_design_scores_gemma":[0.00004787325,0.000006495535,0.000008250005,0.00000933184,0.00001491905,0.000009475678,0.00002700647,0.5213632,0.000008416958,0.4434457,0.03500387,0.0000554881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001495104,0.0003894904,0.9937689,0.001810582,0.00008577815,0.0004726484,0.00001151817,0.0001965515,0.003249625],"genre_scores_gemma":[0.003095889,0.00007559654,0.9955849,0.0001771028,0.0000892621,0.0005213424,0.00002581912,0.00002165912,0.0004084258],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3973551,"threshold_uncertainty_score":0.300076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05465722513684081,"score_gpt":0.3806338186845009,"score_spread":0.3259765935476601,"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."}}