{"id":"W2088159177","doi":"10.1002/mrm.21244","title":"Modeling pulsed magnetization transfer","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Magnetization transfer; Experimental data; Magnetization; Relaxation (psychology); Representation (politics); Biological system; Nuclear magnetic resonance; Physics; Algorithm; Computational physics; Materials science; Statistical physics; Computer science; Mathematics; Statistics; Magnetic resonance imaging; Magnetic field","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":[0.0004841113,0.000445075,0.0004626027,0.0003319485,0.0001847643,0.0005501455,0.001178295,0.0008915038,0.001269634],"category_scores_gemma":[0.002524753,0.0002740371,0.0004086833,0.0004292754,0.0003344421,0.0008399533,0.000399623,0.0004835259,0.0004533423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005543068,"about_ca_system_score_gemma":0.0007473585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003007871,"about_ca_topic_score_gemma":0.001651525,"domain_scores_codex":[0.9998286,0.00003607709,0.000009157016,0.00003787544,0.0000737652,0.00001448147],"domain_scores_gemma":[0.9994307,0.0003184552,0.0000784777,0.0000605463,0.00009104692,0.00002065973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007118857,0.00002658185,0.0007543386,0.0001373584,0.00002223328,0.0001417541,0.0001056831,0.9394529,0.02439441,0.01408764,0.00045626,0.02034965],"study_design_scores_gemma":[0.000004489252,0.00002519332,0.0001585704,0.000004892926,0.000006230665,0.0000626193,0.000004820244,0.9944814,0.001799419,0.002536158,0.0009107724,0.000005249799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04564425,0.0002853445,0.9505947,0.0001090877,0.00002601389,0.00005121489,0.0001534179,0.0003799607,0.002755845],"genre_scores_gemma":[0.8046765,0.0009245199,0.1862446,0.0001286311,0.000033934,0.0003729948,0.0004578688,0.000207675,0.006953275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003007871,"threshold_uncertainty_score":0.00598073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02458487046759706,"score_gpt":0.3262387515866379,"score_spread":0.3016538811190408,"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."}}