{"id":"W1503286358","doi":"","title":"Discussion of \"An optimization based method for selection of resonant harmonic filter branch parameters\"","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Selection (genetic algorithm); Harmonic; Filter (signal processing); Computer science; Mathematical optimization; Mathematics; Physics; Acoustics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0005156339,0.0001682327,0.0003663163,0.0001504465,0.00008794185,0.00002050547,0.00005806559,0.0001448444,0.00002364634],"category_scores_gemma":[0.00001242932,0.0001252479,0.0001151262,0.0001927608,0.00002654687,0.0000922043,1.515461e-7,0.00007561758,4.377683e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004440584,"about_ca_system_score_gemma":0.00003543664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000361085,"about_ca_topic_score_gemma":0.00001069593,"domain_scores_codex":[0.998732,0.0002197901,0.0004736019,0.0002075642,0.0001942719,0.0001727719],"domain_scores_gemma":[0.9993835,0.0001408519,0.0001014298,0.0002121328,0.00006239139,0.00009967139],"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":[0.00001101317,0.0000434194,0.000005263327,0.000602656,0.00007134605,1.782747e-7,0.0003238525,0.9246693,0.05487765,0.00004571135,0.00001725249,0.01933241],"study_design_scores_gemma":[0.0007430378,0.0002130494,0.00001676465,0.0002964922,0.00007556084,0.00002011584,0.0002871526,0.9343879,0.06315172,0.000009022,0.0006279815,0.0001711782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01079823,0.0001157682,0.9874567,0.00001309164,0.0005264053,0.0006424895,0.00004372979,0.00005950953,0.0003441017],"genre_scores_gemma":[0.9951155,0.00002370982,0.004513957,0.000008296039,0.00001307645,0.0001156647,0.000006268526,0.00003808556,0.0001654472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9843172,"threshold_uncertainty_score":0.5107461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01913790835553229,"score_gpt":0.2359308221881336,"score_spread":0.2167929138326013,"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."}}