{"id":"W2028491648","doi":"10.1002/mrm.20145","title":"Accelerating cardiac cine 3D imaging using <i>k‐t</i> BLAST","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eurostars; Canadian Institutes of Health Research; Kommission für Technologie und Innovation","keywords":"Nuclear medicine; Cardiac imaging; Nuclear magnetic resonance; Computer science; Medicine; Physics; Radiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002914284,0.0002262251,0.0005080629,0.0001700138,0.00009795801,0.00000922922,0.0001284178,0.00006400218,0.000146426],"category_scores_gemma":[0.0001521748,0.0001913912,0.00005266957,0.0006585298,0.0002712706,0.0000867686,0.00005928676,0.0003576803,0.000009835847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002005921,"about_ca_system_score_gemma":0.00009121276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003873596,"about_ca_topic_score_gemma":0.0000151112,"domain_scores_codex":[0.9982775,0.00002016505,0.0005176282,0.0004249062,0.0003389179,0.0004209071],"domain_scores_gemma":[0.9991386,0.00005544459,0.00009418179,0.0004743549,0.0000981767,0.0001392577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001608571,0.0003353732,0.05444961,0.0001753127,0.000006134709,0.000448638,0.00114953,0.001754135,0.2017469,0.003720819,0.002155436,0.7338972],"study_design_scores_gemma":[0.02883292,0.003162622,0.2197043,0.01834087,0.0005814504,0.001485511,0.003402569,0.04402735,0.02686585,0.01832303,0.6328934,0.002380075],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7009087,0.1144455,0.1142394,0.02871811,0.0005935786,0.003996308,0.00002260186,0.0007764926,0.03629936],"genre_scores_gemma":[0.6813671,0.003438231,0.3097718,0.00337537,0.001113211,0.0002035167,0.0000309755,0.00009505462,0.0006047174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7315171,"threshold_uncertainty_score":0.7804704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02900100400978175,"score_gpt":0.331238861883126,"score_spread":0.3022378578733443,"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."}}