{"id":"W1557870773","doi":"10.1002/mrm.25164","title":"Robust cardiac BOLD MRI using an fMRI‐like approach with repeated stress paradigms","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute; Université de Montréal; University of Calgary","funders":"Siemens; Siemens USA","keywords":"Magnetic resonance imaging; Computer science; Artificial intelligence; Medicine; Radiology","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":[0.0006197196,0.0007690496,0.0003294598,0.0002727224,0.0001716087,0.0002921545,0.0003758943,0.0006173262,0.0006341578],"category_scores_gemma":[0.001346083,0.0003136045,0.0004422787,0.0001494486,0.0003205164,0.000278093,0.0003204492,0.0004191609,0.0001838918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001328783,"about_ca_system_score_gemma":0.0002429844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004232623,"about_ca_topic_score_gemma":0.001424658,"domain_scores_codex":[0.9998529,0.00004623164,0.00000825275,0.00005427982,0.00002714233,0.00001111968],"domain_scores_gemma":[0.999792,0.00006267071,0.00005036406,0.00004139319,0.00003417218,0.00001928233],"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":[0.0003353946,0.00008311782,0.002552278,0.0001835137,0.0001731165,0.0001570238,0.00009928689,0.006415217,0.9504439,0.0003106151,0.0001912765,0.03905534],"study_design_scores_gemma":[0.0002639398,0.005782016,0.1545483,0.00007001642,0.0006948709,0.004087685,0.0001074676,0.2300338,0.595726,0.0050877,0.003373651,0.0002245315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5368405,0.0007211707,0.4603805,0.000219953,0.00005852738,0.0002404633,0.0002611875,0.0006492536,0.0006283909],"genre_scores_gemma":[0.7678276,0.000366833,0.2301984,0.0001435421,0.00008181037,0.0003820503,0.0003975045,0.000129075,0.0004731533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007690496,"threshold_uncertainty_score":0.003277481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03735978916826156,"score_gpt":0.2932995615972718,"score_spread":0.2559397724290102,"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."}}