{"id":"W1800044634","doi":"10.1109/ccece.2001.933681","title":"Optimal active power flow solutions using a modified Hopfield neural network","year":2002,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Hopfield network; Artificial neural network; Mathematical optimization; Nonlinear programming; Nonlinear system; Computer science; Function (biology); Quadratic programming; Flow (mathematics); Quadratic function; Quadratic equation; Control theory (sociology); Mathematics; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006284286,0.0001260352,0.000129941,0.00003298438,0.0001318277,0.00003788929,0.0001001067,0.00009879532,0.001116047],"category_scores_gemma":[0.000009734603,0.0001304423,0.00007734804,0.0001474318,0.00002401419,0.0001903695,0.00003724485,0.000232445,0.00006731082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003821291,"about_ca_system_score_gemma":0.0000047392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001683036,"about_ca_topic_score_gemma":0.00001224401,"domain_scores_codex":[0.9992166,0.00001959771,0.0001481882,0.000121876,0.00009828879,0.0003955208],"domain_scores_gemma":[0.9996691,0.00004205998,0.00001354939,0.0001730004,0.00001806744,0.00008418478],"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":[0.000004481406,0.00001786737,0.000003112196,0.000004310167,0.00003613399,0.000005029338,0.0003879728,0.988001,0.0002369999,0.001375021,0.009015756,0.0009122888],"study_design_scores_gemma":[0.0001646151,0.00001521522,0.00004773195,0.000006610926,0.00001415845,0.000009158849,0.00008704474,0.9978119,0.0001834257,0.000110783,0.001375665,0.0001737328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3648073,0.001248545,0.4890053,0.0006164433,0.001901237,0.0002871726,0.00003348889,0.00126096,0.1408395],"genre_scores_gemma":[0.9899797,0.00002461131,0.009326846,0.0002100453,0.0001316288,0.000004357482,0.000002628568,0.00002096176,0.0002991744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6251724,"threshold_uncertainty_score":0.999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08240634522999755,"score_gpt":0.2486126368177417,"score_spread":0.1662062915877441,"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."}}