{"id":"W2126750265","doi":"10.1109/tns.2003.817388","title":"Application of reconstruction techniques to correctly identify the myocardium in the presence of overlying organs","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Collimator; Imaging phantom; Iterative reconstruction; Attenuation; Monte Carlo method; Image quality; Correction for attenuation; Image resolution; Computer science; Computer vision; Artificial intelligence; Medical physics; Nuclear medicine; Physics; Biomedical engineering; Optics; Image (mathematics); Mathematics; Medicine","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":[0.0009434797,0.00006543059,0.0001150091,0.0001583579,0.0001666787,0.00001689592,0.0003231207,0.00003509772,0.00002966786],"category_scores_gemma":[0.00007731873,0.00004198914,0.00004741548,0.001411977,0.0005405147,0.0001007516,0.000002016549,0.0002146967,0.000008334999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004260775,"about_ca_system_score_gemma":0.00008038186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001060189,"about_ca_topic_score_gemma":0.00000692255,"domain_scores_codex":[0.9989849,0.00004905235,0.0002369634,0.000204013,0.000395394,0.0001297149],"domain_scores_gemma":[0.9991406,0.0001029846,0.00007785975,0.0005047199,0.0001247887,0.00004901983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003347425,0.0003118762,0.0002614149,0.0000400207,0.000007496786,7.019007e-7,0.001848276,0.0003019439,0.8795485,0.002958541,0.0005289009,0.1141589],"study_design_scores_gemma":[0.0003021432,0.000416551,0.007029074,0.0003472424,0.00007820652,0.0002412969,0.002689965,0.01617864,0.9643614,0.0007005385,0.007466665,0.0001882894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5319258,0.000005975898,0.4607452,0.003949099,0.0001430739,0.001230671,0.000005584128,0.00007585714,0.001918784],"genre_scores_gemma":[0.9846539,0.00002635165,0.01480038,0.0004047807,0.000007461785,0.00007643443,5.488112e-8,0.000006999885,0.00002363199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4527281,"threshold_uncertainty_score":0.1991549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01900106199043976,"score_gpt":0.3129300644054681,"score_spread":0.2939290024150283,"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."}}