{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002323926,0.0001349287,0.0001318507,0.00006403082,0.0001798559,0.00004945898,0.00004994161,0.00009248536,0.00001580575],"category_scores_gemma":[0.0001199686,0.0001338665,0.00002494511,0.0002221303,0.000006485018,0.0001461871,7.57052e-7,0.0001642384,7.520959e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000306003,"about_ca_system_score_gemma":0.00004077132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001703549,"about_ca_topic_score_gemma":0.00003152691,"domain_scores_codex":[0.9990497,0.00005409314,0.0002472615,0.0002229639,0.0002548538,0.0001711745],"domain_scores_gemma":[0.9994985,0.0001608922,0.00003565314,0.00007524685,0.00009741257,0.0001323141],"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":[0.0001312543,0.00006301664,0.0002223775,0.00030593,0.0000415236,9.118045e-7,0.0004902881,0.001117753,0.9689655,0.000006919472,0.00003023219,0.02862431],"study_design_scores_gemma":[0.0006860885,0.0008456231,0.0003114656,0.00006527707,0.00003758589,0.000005501253,0.00001445092,0.2638088,0.7340416,0.00004911151,0.000008666429,0.0001257858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3997817,0.0000352697,0.598592,0.0008420807,0.00007439559,0.0005606757,0.000001032349,0.0001003463,0.00001248206],"genre_scores_gemma":[0.9982922,0.00003088686,0.001247021,0.0002527086,0.00003978659,0.0001119515,0.000002626986,0.00001600389,0.000006832197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5985105,"threshold_uncertainty_score":0.5458918,"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."}}