{"id":"W2517588678","doi":"10.1109/mwsym.2016.7539963","title":"Parallel EM optimization approach to microwave filter design using feature assisted neuro-transfer functions","year":2016,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Maxima and minima; Feature (linguistics); Transfer function; Computer science; Filter (signal processing); Optimization problem; Mathematical optimization; Global optimization; Algorithm; Mathematics; Engineering","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":[0.0000935905,0.0002429883,0.0001734773,0.0001526745,0.00006614169,0.00006380329,0.0001182399,0.0001362308,0.00008122573],"category_scores_gemma":[0.00002554503,0.0001800017,0.00007686341,0.0002601111,0.000011938,0.0001407295,0.00001686509,0.0001132291,0.00004310131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007663453,"about_ca_system_score_gemma":0.00001248765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002431578,"about_ca_topic_score_gemma":0.000001521281,"domain_scores_codex":[0.9990739,0.00002930243,0.0001866399,0.0002701096,0.0001085339,0.0003315598],"domain_scores_gemma":[0.9994714,0.00005860986,0.000007225596,0.0002729921,0.00005351218,0.0001363066],"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":[0.000008452331,0.00001538419,0.000005952943,0.00001860501,0.00003555125,0.000001387442,0.0000775759,0.8226022,0.1663212,0.0000422085,0.009679763,0.00119173],"study_design_scores_gemma":[0.0004906449,0.00003132323,0.0002052801,0.0000567546,0.00004347747,0.00006239051,0.00003280534,0.979397,0.01592718,0.000006346496,0.003277102,0.0004696954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002679598,0.0000625095,0.9936866,0.00009582143,0.0003044834,0.0002627592,0.00001389391,0.0005956856,0.002298678],"genre_scores_gemma":[0.3607785,0.00001397684,0.6353202,0.0001366801,0.0001399118,0.00002776284,0.00001673836,0.00009554721,0.003470558],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3583663,"threshold_uncertainty_score":0.7340258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993359378219541,"score_gpt":0.204371039492476,"score_spread":0.1744374457102806,"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."}}