{"id":"W1964792401","doi":"10.1118/1.1582812","title":"A dynamic approach to identifying desired physiological phases for cardiac imaging using multislice spiral CT","year":2003,"lang":"en","type":"article","venue":"Medical Physics","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Continental (Canada)","funders":"","keywords":"Cardiac cycle; Multislice; Cardiac imaging; Coronary arteries; Image quality; Right coronary artery; Spiral (railway); Artery; Circumflex; Medicine; Biomedical engineering; Nuclear medicine; Artificial intelligence; Radiology; Computer science; Cardiology; Mathematics; Coronary angiography; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004484486,0.0002670677,0.0006335538,0.00005959833,0.0001738273,0.00004602129,0.0001210926,0.00005869892,0.00001277933],"category_scores_gemma":[0.002821859,0.0002337989,0.0004082104,0.0003116052,0.0001608711,0.00008938472,0.00006520931,0.0002952322,0.00001627675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000145832,"about_ca_system_score_gemma":0.0002175627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004282339,"about_ca_topic_score_gemma":2.616798e-7,"domain_scores_codex":[0.9978777,0.0000843765,0.0003180677,0.0005134605,0.0006236475,0.0005827622],"domain_scores_gemma":[0.9985757,0.0003794509,0.00006797667,0.0003428471,0.0001352958,0.0004987653],"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":[0.001187889,0.01545348,0.1946041,0.004548456,0.002501694,0.001381588,0.004365518,0.004894824,0.2076596,0.00727948,0.06025548,0.4958679],"study_design_scores_gemma":[0.0521057,0.001711358,0.08931895,0.0057103,0.00866692,0.002059196,0.004831374,0.6192438,0.1520068,0.01682632,0.03929707,0.008222249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3859128,0.0007349006,0.6096362,0.0001748472,0.0008039647,0.0009308505,0.00004050677,0.0001800074,0.001585894],"genre_scores_gemma":[0.9735413,0.00001351021,0.02404369,0.001600544,0.0005253807,0.00008146818,0.00008451864,0.00005224481,0.00005736497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6143489,"threshold_uncertainty_score":0.9534042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06792774164430257,"score_gpt":0.3547590297453196,"score_spread":0.286831288101017,"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."}}