{"id":"W2130703866","doi":"10.1109/tmi.2011.2179944","title":"Catheter Tracking With Phase Information in a Magnetic Resonance Scanner","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Catheter; Electromagnetic coil; Redundancy (engineering); Tracking (education); Magnetic resonance imaging; Scanner; Orientation (vector space); Computer science; Computer vision; Position (finance); Artificial intelligence; A priori and a posteriori; Biomedical engineering; Radiology; Physics; Medicine; Mathematics","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":[0.0001220248,0.0001134336,0.0001422394,0.0001803515,0.00006678796,0.000009483698,0.00007530142,0.00005153525,0.0004584049],"category_scores_gemma":[0.000009305402,0.00008983796,0.00004219236,0.0002782724,0.0001335331,0.0003196524,7.372774e-7,0.0003921593,0.00002798431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005767098,"about_ca_system_score_gemma":0.00006872459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008088973,"about_ca_topic_score_gemma":0.00002710237,"domain_scores_codex":[0.999077,0.00001316735,0.0002537636,0.0001543887,0.000291804,0.0002098557],"domain_scores_gemma":[0.9995152,0.00002590551,0.00003684457,0.0002083398,0.00005475021,0.0001588984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002289502,0.0007361952,0.0001619805,0.0000193616,0.00000245157,0.00005535143,0.0009986378,0.0000430427,0.0002736896,0.00008541382,0.00007837374,0.9973165],"study_design_scores_gemma":[0.06342699,0.007287339,0.01556635,0.009680651,0.0008332375,0.005219764,0.005636381,0.4064052,0.3052539,0.004184618,0.1730134,0.00349217],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02136284,0.00009113109,0.9747313,0.001136098,0.0000403647,0.0003493185,0.000006534543,0.0001459515,0.00213641],"genre_scores_gemma":[0.9777989,0.00007969794,0.02036068,0.001437036,0.00001987919,0.0001841339,0.000003703497,0.0000162727,0.00009965939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9938244,"threshold_uncertainty_score":0.5019212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01834365175406168,"score_gpt":0.300518166282814,"score_spread":0.2821745145287524,"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."}}