{"id":"W2904801499","doi":"10.1109/antem.2018.8572920","title":"Multi-Plane Magnetic Near-Field Data Inversion Using the Source Reconstruction Method","year":2018,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Compatibility and Measurements","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"CMC Microsystems","keywords":"Planar; Magnetic field; Ground plane; Antenna (radio); Plane (geometry); Computer science; Near and far field; Acoustics; Physics; Optics; Mathematics; Geometry; Telecommunications","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":[0.0003624518,0.0000913215,0.0000837857,0.00002741291,0.0001452006,0.00004270397,0.0002722895,0.0000535459,0.0006485468],"category_scores_gemma":[0.00005922937,0.00007032261,0.00001620785,0.0001349405,0.00004822274,0.0001031074,0.00007887206,0.0001346745,0.00003847748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002797815,"about_ca_system_score_gemma":0.00001815974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004959749,"about_ca_topic_score_gemma":0.0005987377,"domain_scores_codex":[0.9993128,0.0000611841,0.0001416631,0.0001830062,0.0001223705,0.0001789979],"domain_scores_gemma":[0.9992431,0.00006767048,0.0000165766,0.0005963982,0.00003466182,0.00004152824],"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":[0.00002805691,0.00003576662,0.00169533,0.00005267021,0.00004379149,8.855508e-7,0.0006729212,0.001145635,0.3647754,0.000007910605,0.004695733,0.6268459],"study_design_scores_gemma":[0.0002410419,0.0001191625,0.0004547583,0.0000176731,0.00003110781,0.00003303615,0.0001156388,0.96162,0.03054382,0.00002337513,0.006695634,0.0001046894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.59152,0.0001502896,0.4043608,0.0001063283,0.0005733778,0.0001989946,0.00000299817,0.0001984481,0.002888792],"genre_scores_gemma":[0.7022376,0.00002114549,0.2970617,0.0001894122,0.0001691285,0.000001831962,0.000009823746,0.00001853044,0.0002907812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9604744,"threshold_uncertainty_score":0.7101133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0693973698577416,"score_gpt":0.2874770965950658,"score_spread":0.2180797267373242,"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."}}