{"id":"W3000407218","doi":"10.1109/tap.2020.2963940","title":"Electric Field Probe Used for Gradient Coil-Induced Field Measurements During Medical Device Testing: Design, Calibration, and Validation","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Electromagnetic Compatibility and Measurements","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Research Foundation; CMC Microsystems","keywords":"Electromagnetic coil; Materials science; Calibration; Dipole; Conductor; Instrumentation (computer programming); Imaging phantom; Electrical conductor; Electric field; Optics; Antenna (radio); Amplifier; Dipole antenna; Acoustics; Nuclear magnetic resonance; Optoelectronics; Electrical engineering; Physics; Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626535,0.0006837223,0.0004562833,0.0005069891,0.0002053969,0.0005182109,0.001019906,0.00101914,0.001532577],"category_scores_gemma":[0.003560157,0.0002398906,0.0001983033,0.0003625261,0.0006881836,0.0006994045,0.0005840509,0.0004180233,0.0006497047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003338986,"about_ca_system_score_gemma":0.0005061327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001749297,"about_ca_topic_score_gemma":0.0002182335,"domain_scores_codex":[0.9989821,0.0003105249,0.00007348503,0.0001593135,0.0004136501,0.00006095268],"domain_scores_gemma":[0.9983108,0.0006410488,0.0002304711,0.0002836709,0.0004613672,0.00007251451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004170735,0.0001094998,0.002591196,0.0009007833,0.00003661864,0.0004581119,0.0003768108,0.003663903,0.9051542,0.002251164,0.001738444,0.08230226],"study_design_scores_gemma":[0.00005821466,0.00170733,0.004105046,0.00008103065,0.00005815317,0.001820291,0.0001237234,0.01584844,0.9546981,0.0006853932,0.02076052,0.00005374362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1133378,0.001308395,0.8797142,0.0003581965,0.000253075,0.0008223612,0.0002836907,0.002123157,0.00179919],"genre_scores_gemma":[0.6246178,0.001072579,0.3696047,0.0003253196,0.00006526426,0.001159702,0.0003208724,0.000222034,0.00261174],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001626535,"threshold_uncertainty_score":0.008602023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07981655760372468,"score_gpt":0.2529299564205222,"score_spread":0.1731133988167975,"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."}}