{"id":"W1978532820","doi":"10.1007/s10334-003-0024-6","title":"High-resolution imaging at 3T and 7T with multiring local volume coils","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; National Research Council Canada; National Research Council Institute for Biodiagnostics","funders":"","keywords":"Electromagnetic coil; Radio frequency; Magnetic resonance imaging; Nuclear magnetic resonance; Resolution (logic); Materials science; RF power amplifier; Radiofrequency coil; High resolution; Volume (thermodynamics); Magnetic field; Physics; Computer science; Optoelectronics; Geology; Telecommunications; Radiology; Medicine; Remote sensing; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001364809,0.0001581447,0.0003659696,0.00004041644,0.00008630832,0.000003914839,0.00004077064,0.00007056867,0.00003539439],"category_scores_gemma":[0.00001936145,0.000113382,0.000008246873,0.0001002463,0.000844228,0.00003727443,0.00006411236,0.00009727651,0.00000289985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005868385,"about_ca_system_score_gemma":0.00001897757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00036419,"about_ca_topic_score_gemma":0.00002505118,"domain_scores_codex":[0.9991155,0.0000221933,0.0002355014,0.0003227947,0.00006433782,0.0002397342],"domain_scores_gemma":[0.9996126,0.00002906372,0.00006972098,0.0001814387,0.00003616503,0.00007097285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009081626,0.0001517841,0.01538684,0.0001764938,0.000006888721,0.0000717046,0.0004543581,0.00009735661,0.6692371,0.05003221,0.0001515374,0.2633255],"study_design_scores_gemma":[0.02942693,0.005939093,0.4388258,0.004001086,0.000309878,0.001105032,0.0005611795,0.00152993,0.3060345,0.1709301,0.04012088,0.001215544],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414456,0.006130996,0.04853571,0.0030159,0.00007523222,0.0005218054,0.00001860424,0.00006594668,0.0001901642],"genre_scores_gemma":[0.9851101,0.001864745,0.01204656,0.0004513355,0.0002302724,0.00009688804,0.00005110185,0.00001611968,0.0001328465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.423439,"threshold_uncertainty_score":0.4623584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008402218981830358,"score_gpt":0.2786325866953342,"score_spread":0.2702303677135038,"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."}}