{"id":"W3203618776","doi":"10.1109/aces53325.2021.00108","title":"Design and Modelling of Metamaterial Resonators for 3 Tesla Magnetic Resonance Imaging","year":2021,"lang":"en","type":"article","venue":"2021 International Applied Computational Electromagnetics Society Symposium (ACES)","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Resonator; Metamaterial; Sensitivity (control systems); Resonance (particle physics); Dispersion (optics); Acoustics; Transmission line; Materials science; Split-ring resonator; Magnetic resonance imaging; Nuclear magnetic resonance; Physics; Optics; Electronic engineering; Computer science; Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002272424,0.0004905272,0.000418155,0.0001635965,0.0001674484,0.0005427736,0.0008376508,0.001101662,0.002034582],"category_scores_gemma":[0.0003473662,0.0003573808,0.0005688109,0.0001524207,0.0002368484,0.000418107,0.0002508183,0.0003762519,0.001287591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004930226,"about_ca_system_score_gemma":0.0005755356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007949516,"about_ca_topic_score_gemma":0.001241885,"domain_scores_codex":[0.9998902,0.0000225265,0.000003713473,0.00001736823,0.00005100387,0.00001523235],"domain_scores_gemma":[0.9998881,0.00003634009,0.00002605057,0.00001765121,0.000023697,0.000008100733],"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":[0.0001238573,0.00007111009,0.000628554,0.0002577899,0.00004164871,0.0003917519,0.0001745606,0.6291301,0.3311294,0.01940613,0.001590348,0.01705485],"study_design_scores_gemma":[0.00001314293,0.00008288671,0.0003161642,0.00001848042,0.00001296874,0.0001317913,0.00002729302,0.9563633,0.03254836,0.001330016,0.009134358,0.00002123026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06330618,0.0004175887,0.9158654,0.0003238663,0.00006191283,0.0001217199,0.0003428548,0.0008584943,0.0187021],"genre_scores_gemma":[0.4392212,0.0005671309,0.5457857,0.0000974555,0.00002495759,0.0003551124,0.000281655,0.0003448805,0.01332202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002034582,"threshold_uncertainty_score":0.006806314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008220131450686037,"score_gpt":0.198808011866822,"score_spread":0.190587880416136,"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."}}