{"id":"W2328671016","doi":"10.1186/1532-429x-18-s1-p206","title":"Intrinsic MRI visualizes RF lesions within minutes after MR-guided ablation","year":2016,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Angiology; Ablation; Radiology; Magnetic resonance imaging; Rf ablation; Radiofrequency ablation; Nuclear medicine; Biomedical engineering; Medical physics; Internal medicine","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":[0.0002523804,0.0004347024,0.0002256053,0.0006799783,0.0002240745,0.0006427146,0.0003339687,0.001807677,0.002689819],"category_scores_gemma":[0.001157884,0.0002678587,0.0002446103,0.0002510987,0.0003114574,0.0006989737,0.0003573624,0.001942307,0.0009918663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817575,"about_ca_system_score_gemma":0.0002433936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006006492,"about_ca_topic_score_gemma":0.001215415,"domain_scores_codex":[0.9999232,0.00001288877,0.000004312466,0.000008887543,0.00001553281,0.00003517912],"domain_scores_gemma":[0.999335,0.000251419,0.000129501,0.00006120287,0.00007813616,0.0001447242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.007133772,0.0004069359,0.00609246,0.0005084129,0.0001207493,0.01833291,0.0004378183,0.000869507,0.9069351,0.002041325,0.006334253,0.0507868],"study_design_scores_gemma":[0.0006703424,0.007715608,0.1792544,0.000381619,0.0003597915,0.05147387,0.0005419396,0.01148804,0.7045075,0.003625729,0.03979486,0.0001863552],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8928604,0.01277084,0.05643012,0.004088011,0.0008685991,0.0002637223,0.0007746459,0.001617034,0.03032662],"genre_scores_gemma":[0.9792227,0.002387537,0.01014775,0.0007418405,0.0007504283,0.00008997924,0.0005447032,0.0001944521,0.005920552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002689819,"threshold_uncertainty_score":0.008998334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684739057598686,"score_gpt":0.2844680273395094,"score_spread":0.2676206367635226,"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."}}