{"id":"W2743481168","doi":"10.1002/mmce.21157","title":"A decoupled source current reconstruction method for noisy and reactive near-field to far-field transformation","year":2017,"lang":"en","type":"article","venue":"International Journal of RF and Microwave Computer-Aided Engineering","topic":"Electromagnetic Compatibility and Measurements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alberta","keywords":"Tikhonov regularization; Transformation (genetics); Field (mathematics); Noise (video); Integral equation; Algorithm; Current (fluid); Mathematics; Mathematical analysis; Computer science; Physics; Inverse problem; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000553218,0.0006881177,0.0005284846,0.0006917669,0.0003226361,0.0007174364,0.001134445,0.0007834316,0.0036809],"category_scores_gemma":[0.001490511,0.0004032991,0.0008541616,0.0006577179,0.0003766914,0.001694892,0.0007694707,0.0009644135,0.001966769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003398168,"about_ca_system_score_gemma":0.0009201869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000940744,"about_ca_topic_score_gemma":0.001242315,"domain_scores_codex":[0.9996232,0.00005716838,0.00002270594,0.00005268391,0.0002287889,0.000015359],"domain_scores_gemma":[0.9996024,0.00009354961,0.00004829143,0.00008799662,0.0001498987,0.00001798427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001857341,0.0001274732,0.001071268,0.0004485048,0.0001007225,0.000294186,0.0004206965,0.1784689,0.1339007,0.06341603,0.005068047,0.6164976],"study_design_scores_gemma":[0.00002758151,0.00004232161,0.0002028725,0.00001496063,0.00001666674,0.0002871194,0.000033641,0.9682915,0.01799525,0.004822135,0.008234601,0.00003133148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009120677,0.0000361893,0.998296,0.00002464368,0.00001426782,0.00001253496,0.000009173759,0.0001735505,0.0005216349],"genre_scores_gemma":[0.04476302,0.0001855123,0.951427,0.00006211006,0.00003104686,0.00008693337,0.0001614821,0.0001744372,0.00310839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0036809,"threshold_uncertainty_score":0.0123139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01238913790340019,"score_gpt":0.2688975009967124,"score_spread":0.2565083630933123,"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."}}