{"id":"W1986061044","doi":"10.1002/mrm.21711","title":"Free‐breathing cine MRI","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta Hospital; Alberta Hospital Edmonton; University of Alberta","funders":"","keywords":"Breathing; Cartesian coordinate system; Computer science; Nuclear medicine; Magnetic resonance imaging; Computer vision; Motion (physics); Standard deviation; Artificial intelligence; Biomedical engineering; Medicine; Mathematics; Radiology; Anatomy; Geometry","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":[0.0002047697,0.0001801577,0.0004351171,0.0001671108,0.00008490348,0.000001830445,0.0001993337,0.00009230675,0.0005708918],"category_scores_gemma":[0.0002646081,0.0001411681,0.0000415108,0.0005599287,0.0003889515,0.00004981625,0.00006321446,0.0003416991,0.00002034918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007109189,"about_ca_system_score_gemma":0.00004885155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001937402,"about_ca_topic_score_gemma":0.0000157915,"domain_scores_codex":[0.9985116,0.00001856832,0.0004336819,0.0003610398,0.0003505215,0.0003246074],"domain_scores_gemma":[0.9988729,0.00008751453,0.00006269602,0.0007584603,0.00007561815,0.0001427666],"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":[0.0006045771,0.001001335,0.1239846,0.0002677819,0.000009013286,0.004741318,0.004004982,0.00009963771,0.02264168,0.01486517,0.3020974,0.5256826],"study_design_scores_gemma":[0.005372386,0.001396059,0.2488768,0.001005139,0.00003937936,0.001691002,0.0002089711,0.001673412,0.001092321,0.00598792,0.7323642,0.0002923481],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4345666,0.1399155,0.06977534,0.1439305,0.0004844549,0.004839866,0.00003903314,0.001386537,0.2050621],"genre_scores_gemma":[0.7106705,0.02952807,0.2189319,0.008367371,0.001485565,0.0006447315,0.00006220416,0.0001255005,0.03018419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5253903,"threshold_uncertainty_score":0.6250864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02636566429191071,"score_gpt":0.3148352490784196,"score_spread":0.2884695847865089,"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."}}