{"id":"W2045984953","doi":"10.1088/0031-9155/50/14/008","title":"Rigid-body transformation of list-mode projection data for respiratory motion correction in cardiac PET","year":2005,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Computer science; Image quality; Imaging phantom; Computer vision; Detector; Artificial intelligence; Projection (relational algebra); Nuclear medicine; Algorithm; Medicine; 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":[0.00055221,0.00006971592,0.0002581389,0.0001077469,0.00002073277,0.000001207872,0.00005553161,0.00005615694,0.000005454301],"category_scores_gemma":[0.0001318055,0.00005391305,0.00001870735,0.0001869161,0.0001206206,0.00008776897,0.000015438,0.0001468655,3.41723e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003657768,"about_ca_system_score_gemma":0.00003165134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003915464,"about_ca_topic_score_gemma":0.00006469437,"domain_scores_codex":[0.9993181,0.00004206839,0.0002942386,0.0001872036,0.00005683625,0.0001015549],"domain_scores_gemma":[0.9995454,0.00008972549,0.00007363266,0.000208467,0.00005312154,0.00002967252],"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":[0.0003552662,0.0006692062,0.0238146,0.0005690611,0.00003961776,8.622918e-7,0.001450141,0.00001967472,0.255965,0.02046252,0.01450345,0.6821505],"study_design_scores_gemma":[0.009828595,0.003010519,0.01847006,0.001451327,0.0003937906,0.0000420456,0.001334336,0.5325698,0.04671999,0.01674183,0.368925,0.0005126819],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7441052,0.0004550352,0.2305363,0.01919329,0.0004646674,0.002568284,0.0001112656,0.0001057563,0.002460269],"genre_scores_gemma":[0.9955024,0.0003528609,0.002437889,0.0003997672,0.0005101483,0.00009847079,0.0006744369,0.000006205602,0.00001782474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6816379,"threshold_uncertainty_score":0.219851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2362232969440644,"score_gpt":0.4691764000225767,"score_spread":0.2329531030785122,"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."}}