{"id":"W2253627718","doi":"10.1016/j.mri.2015.12.032","title":"Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Quantitative susceptibility mapping; Globus pallidus; Computer science; Neuroscience; Gray (unit); Physics; Psychology; Magnetic resonance imaging; Basal ganglia; Medicine; Nuclear medicine","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":[0.0002836798,0.0001652973,0.0003859648,0.00008859867,0.00003909328,0.000007977765,0.0001478039,0.00002664913,0.00004974896],"category_scores_gemma":[0.0002540457,0.0001571488,0.0000928701,0.000229476,0.0002455816,0.00009399709,0.0000643326,0.0001236642,0.00000407718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005483817,"about_ca_system_score_gemma":0.00006925211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007625006,"about_ca_topic_score_gemma":0.0000123283,"domain_scores_codex":[0.998544,0.00003026957,0.0005266221,0.0003988571,0.0002384023,0.0002617931],"domain_scores_gemma":[0.9986094,0.000135116,0.0002709625,0.0005523664,0.000345883,0.00008632908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003732615,0.0003122788,0.859687,0.0004085687,0.00000565021,0.00001240637,0.0006790973,0.00002896769,0.04378657,0.001336658,0.00205463,0.09131492],"study_design_scores_gemma":[0.002795292,0.0006001082,0.9370912,0.0002976716,0.0000770312,0.00004666824,0.000434928,0.01566885,0.01551964,0.0159958,0.01112688,0.0003459571],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6056538,0.003830603,0.385314,0.001601069,0.00006994056,0.001452322,0.00006631001,0.00008794661,0.001924055],"genre_scores_gemma":[0.8664926,0.00004244968,0.1327375,0.0003118071,0.00003179327,0.0001121165,0.00001793841,0.00002978755,0.000224055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2608387,"threshold_uncertainty_score":0.6408342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0532588597182677,"score_gpt":0.3459175589204995,"score_spread":0.2926586992022318,"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."}}