{"id":"W2050750752","doi":"10.1016/j.mri.2006.09.046","title":"The effect of varying echo spacing within a multiecho acquisition: better characterization of long T2 components","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Sunnybrook Health Science Centre","funders":"Killam Trusts; Multiple Sclerosis Society of Canada","keywords":"T2 relaxation; Imaging phantom; Echo (communications protocol); Nuclear magnetic resonance; Echo time; Relaxation (psychology); Pulse (music); In vivo; Pulse sequence; White matter; Distribution (mathematics); Myelin; Nuclear medicine; Chemistry; Magnetic resonance imaging; Biomedical engineering; Mathematics; Medicine; Physics; Radiology; Optics; Computer science; Central nervous system; Biology; Mathematical analysis","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":[0.0009907963,0.0007050144,0.0003886442,0.0003951787,0.0003248602,0.0007694403,0.0003611184,0.00153302,0.001503094],"category_scores_gemma":[0.003723497,0.0004655014,0.0002144348,0.0004470092,0.0005167294,0.001254966,0.0003640734,0.000940683,0.0003424074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009500228,"about_ca_system_score_gemma":0.0002189223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003083792,"about_ca_topic_score_gemma":0.0006578283,"domain_scores_codex":[0.9997532,0.00009454798,0.00001924344,0.00006388505,0.00004481729,0.00002444602],"domain_scores_gemma":[0.9974927,0.001670937,0.0002171049,0.0002972781,0.0001769357,0.0001451041],"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":[0.0008730233,0.00008355887,0.0007884149,0.0001056593,0.00003045091,0.0001277911,0.00008395714,0.001487743,0.9865607,0.0001244778,0.00008937174,0.009644819],"study_design_scores_gemma":[0.00006516341,0.0008162484,0.01139804,0.00002083534,0.0001530604,0.001360032,0.00005540926,0.0146938,0.9694905,0.0002074051,0.001691948,0.00004755909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8793141,0.00304847,0.1149383,0.000213358,0.0001007408,0.0000403179,0.0001559321,0.0005834799,0.001605396],"genre_scores_gemma":[0.8738689,0.001463405,0.1217771,0.0002713015,0.0001051009,0.00004726286,0.0002670343,0.0005931691,0.001606703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00153302,"threshold_uncertainty_score":0.005239904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006731558205316015,"score_gpt":0.2747652835077647,"score_spread":0.2680337253024487,"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."}}