{"id":"W3169457050","doi":"10.1002/jmri.27763","title":"Quantitative Susceptibility Mapping for Staging Acute Cerebral Hemorrhages: Comparing the Conventional and <scp>Multiecho</scp> Complex Total Field Inversion magnetic resonance imaging <scp>MR</scp> Methods","year":2021,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Intracerebral and Subarachnoid Hemorrhage Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Medicine; Quantitative susceptibility mapping; Magnetic resonance imaging; Susceptibility weighted imaging; Nuclear medicine; Radiology; Fluid-attenuated inversion recovery; Intracerebral hemorrhage; Gradient echo; Clinical significance; Pathology; Internal medicine; Subarachnoid hemorrhage","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":[0.001639709,0.0003866649,0.0002171546,0.001290787,0.000136157,0.0003566133,0.0002726917,0.0003095265,0.0007298281],"category_scores_gemma":[0.00313621,0.0001519758,0.000205012,0.0003563666,0.0002977117,0.0003910935,0.0002277261,0.000220314,0.0001662205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002192022,"about_ca_system_score_gemma":0.0002650053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004324115,"about_ca_topic_score_gemma":0.0009259445,"domain_scores_codex":[0.9994943,0.0002033637,0.00004715921,0.0001030232,0.0001238519,0.0000282933],"domain_scores_gemma":[0.9985557,0.0004541954,0.0004878683,0.000133527,0.000224579,0.0001441712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00240989,0.0002551684,0.9310164,0.0001314705,0.0002147531,0.0001510412,0.000108455,0.0004874284,0.02281985,0.0001174244,0.0001946027,0.04209355],"study_design_scores_gemma":[0.0001297735,0.003031784,0.9810236,0.00002124102,0.0001793515,0.002143914,0.0001853344,0.005806745,0.006508092,0.0002715365,0.0006702896,0.00002827722],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897289,0.001120771,0.008238824,0.00005790405,0.00001778549,0.00009111237,0.0001978509,0.00003473691,0.0005120542],"genre_scores_gemma":[0.9952385,0.0001735017,0.004252299,0.0000133224,0.00002222262,0.00004998611,0.0001205827,0.000004412208,0.0001251409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001639709,"threshold_uncertainty_score":0.008671701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04248345760559597,"score_gpt":0.3456463169353799,"score_spread":0.303162859329784,"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."}}