{"id":"W1999977619","doi":"10.1002/mrm.1278","title":"Quantitative imaging of magnetization transfer exchange and relaxation properties in vivo using MRI","year":2001,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":412,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Magnetization transfer; Magnetization; Relaxation (psychology); Nuclear magnetic resonance; Relaxometry; Parametric statistics; Magnetic resonance imaging; Materials science; Physics; Spin echo; Mathematics; Radiology; Medicine; Magnetic field; Biology; Statistics; Neuroscience","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":[0.00071115,0.0004831844,0.0003642769,0.0006119066,0.0001577473,0.0003782398,0.0003335715,0.0006063389,0.001126843],"category_scores_gemma":[0.001148005,0.000251912,0.0001255206,0.0002696269,0.0003847206,0.0006793128,0.0002539277,0.0004804534,0.0003845215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008894045,"about_ca_system_score_gemma":0.0001195334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001656597,"about_ca_topic_score_gemma":0.0002400084,"domain_scores_codex":[0.9998322,0.00005766256,0.000007754948,0.00004894197,0.00003863064,0.00001488642],"domain_scores_gemma":[0.9995897,0.000211024,0.00008651453,0.00004241807,0.00003997498,0.00003037641],"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":[0.00009867649,0.00002204037,0.0003760821,0.00006972624,0.000009589264,0.00003946395,0.00002342487,0.0002202874,0.9836654,0.0002620859,0.00005674257,0.01515638],"study_design_scores_gemma":[0.00005028936,0.0009964509,0.01459396,0.00002534139,0.0001117026,0.002998253,0.00005629172,0.01270214,0.9621195,0.001639917,0.004659787,0.00004644401],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5129718,0.009805009,0.4717115,0.0003292026,0.00006650094,0.0001117443,0.0004018997,0.001139072,0.003463342],"genre_scores_gemma":[0.7353544,0.00499513,0.2566965,0.0001299249,0.0001290988,0.0001887071,0.0002477987,0.00012594,0.002132463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001126843,"threshold_uncertainty_score":0.003769696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04273111089418349,"score_gpt":0.3241246305622698,"score_spread":0.2813935196680862,"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."}}