{"id":"W4285293369","doi":"10.1109/lemcpa.2022.3180974","title":"RF Heating Dependence of Head Model Positioning Using 4-Channel Parallel Transmission MRI and a Deep Brain Stimulation Construct","year":2022,"lang":"en","type":"article","venue":"IEEE Letters on Electromagnetic Compatibility Practice and Applications","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McMaster University; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Deep brain stimulation; Imaging phantom; Magnetic resonance imaging; Rotation (mathematics); Sensitivity (control systems); Computer science; Radio frequency; Channel (broadcasting); Biomedical engineering; Materials science; Simulation; Physics; Nuclear magnetic resonance; Nuclear medicine; Medicine; Electronic engineering; Radiology; Telecommunications; Artificial intelligence","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":[0.0002747453,0.0002837424,0.0001312414,0.0001922719,0.0001108909,0.0002879465,0.0002685138,0.0002694923,0.001731606],"category_scores_gemma":[0.0008367534,0.0002223364,0.0001930655,0.0001564367,0.0002519221,0.0003559471,0.0002965862,0.0002253467,0.0003414238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002220157,"about_ca_system_score_gemma":0.0001974228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006588324,"about_ca_topic_score_gemma":0.0009320994,"domain_scores_codex":[0.999887,0.00001399988,0.000006980397,0.00002897254,0.00004234017,0.00002069139],"domain_scores_gemma":[0.9995767,0.0001303491,0.0001171832,0.0000653653,0.0000825452,0.0000278123],"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":[0.0001731013,0.00004003142,0.0005451665,0.00009118276,0.000007538327,0.000132984,0.0001085497,0.0116245,0.9811766,0.0003784343,0.0002120499,0.00550998],"study_design_scores_gemma":[0.00001355257,0.0005837571,0.003204031,0.00001091908,0.00003212106,0.0001731936,0.00006130298,0.03962719,0.953561,0.0001317044,0.002570445,0.00003079405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678609,0.0002489851,0.02863224,0.00009885118,0.00005411161,0.00002672108,0.0001310555,0.0003197071,0.002627514],"genre_scores_gemma":[0.9856539,0.0001601101,0.01265254,0.00002221312,0.000005113151,0.00002245302,0.00009470942,0.00005583259,0.00133301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001731606,"threshold_uncertainty_score":0.005792797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02360016696239654,"score_gpt":0.3286965738211867,"score_spread":0.3050964068587901,"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."}}