{"id":"W1965997320","doi":"10.1002/jmri.20003","title":"Automated image registration of gated cardiac single‐photon emission computed tomography and magnetic resonance imaging","year":2004,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Medical Research Council; Canadian Institutes of Health Research","keywords":"Magnetic resonance imaging; Segmentation; Artificial intelligence; Single-photon emission computed tomography; Thresholding; Image registration; Nuclear medicine; Computer science; Preprocessor; Emission computed tomography; Mutual information; Computer vision; Medicine; Positron emission tomography; Radiology; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001418071,0.0006135105,0.0007898411,0.001329205,0.0002393162,0.0008869193,0.001101111,0.0007205194,0.001344907],"category_scores_gemma":[0.00582614,0.0004347468,0.0007102625,0.0008608749,0.0003880093,0.0004612239,0.0005481105,0.0004641856,0.0007836292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000430872,"about_ca_system_score_gemma":0.0009600715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001701357,"about_ca_topic_score_gemma":0.002544183,"domain_scores_codex":[0.998534,0.0005810063,0.00007739492,0.0002421579,0.000475021,0.00009039378],"domain_scores_gemma":[0.9986736,0.000568394,0.0001773739,0.0002185163,0.0003328794,0.00002932051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001003154,0.0003280236,0.01345464,0.0003538304,0.0003902829,0.0007448074,0.0001954921,0.06871168,0.3172601,0.002357348,0.002718181,0.5924825],"study_design_scores_gemma":[0.0002557364,0.001062425,0.06668282,0.00009872334,0.0002961185,0.004557098,0.0001869114,0.6666394,0.2406702,0.006460242,0.01292614,0.0001641684],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2284402,0.001016104,0.7663481,0.0001659894,0.00008633901,0.0002512212,0.0002937598,0.001855112,0.001543196],"genre_scores_gemma":[0.478665,0.0005661979,0.5170029,0.0001395033,0.00007321742,0.0003997958,0.001296827,0.0003615261,0.001494983],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001701357,"threshold_uncertainty_score":0.007499576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007021108116391947,"score_gpt":0.2477694975710149,"score_spread":0.240748389454623,"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."}}