{"id":"W2148353467","doi":"10.1667/rr2620.1","title":"Principles of Magnetic Resonance Imaging","year":2012,"lang":"en","type":"review","venue":"Radiation Research","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Magnetic resonance imaging; Nuclear magnetic resonance; Simple (philosophy); Medical imaging; Resonance (particle physics); Medical physics; Computer science; Physics; Medicine; Artificial intelligence; Radiology; Philosophy; Atomic physics; Epistemology","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":[0.001724637,0.001231903,0.001348598,0.003658296,0.0009125568,0.00263813,0.001991967,0.002758956,0.004912342],"category_scores_gemma":[0.001768924,0.0005465786,0.0006859308,0.001845552,0.006359073,0.002938534,0.002064834,0.003688562,0.006061262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001373772,"about_ca_system_score_gemma":0.001661642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007361444,"about_ca_topic_score_gemma":0.0007642985,"domain_scores_codex":[0.9983428,0.0003408873,0.0001489854,0.0002206611,0.0008525074,0.00009416012],"domain_scores_gemma":[0.9991241,0.0004140829,0.000084258,0.00007955969,0.0002492992,0.00004871352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000490925,0.00006609313,0.0002369275,0.005463922,0.00004590724,0.0005528083,0.0006315561,0.0009622856,0.007899438,0.4922542,0.05660596,0.4352319],"study_design_scores_gemma":[0.00000681993,0.00003644478,0.0002027008,0.0008558969,0.000009429841,0.001763585,0.00007694081,0.0002185155,0.001640948,0.07537478,0.9197799,0.00003397928],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001182558,0.7594266,0.09327846,0.01334963,0.004975842,0.0001669355,0.0002553011,0.0005464377,0.1268182],"genre_scores_gemma":[0.03050823,0.8115032,0.09285339,0.007911375,0.006286624,0.0008298956,0.0002958262,0.0001573357,0.04965408],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004912342,"threshold_uncertainty_score":0.01643342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2481980412055356,"score_gpt":0.5175333940120954,"score_spread":0.2693353528065598,"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."}}