{"id":"W4248368359","doi":"10.1109/nssmic.1991.259284","title":"Analytic image reconstruction in PVI using the 3D Radon transform","year":2002,"lang":"en","type":"article","venue":"Conference Record of the 1991 IEEE Nuclear Science Symposium and Medical Imaging Conference","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Radon transform; Computation; Fourier transform; Iterative reconstruction; Monte Carlo method; Inversion (geology); Algorithm; Radon; Artificial intelligence; Computer vision; Physics; Computer science; Mathematics; Mathematical analysis; Geology; Statistics; Nuclear physics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001141528,0.000214958,0.0003899977,0.0001944734,0.0003639014,0.000123908,0.0008547637,0.00009576968,0.000521974],"category_scores_gemma":[0.0003861988,0.0001299192,0.0001011348,0.0008635352,0.004617108,0.0003639174,0.0001529693,0.0006985613,0.000007505704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010945,"about_ca_system_score_gemma":0.0003528998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005298108,"about_ca_topic_score_gemma":0.0000349342,"domain_scores_codex":[0.9974437,0.00008209974,0.0005538856,0.0005159609,0.0009120643,0.0004923391],"domain_scores_gemma":[0.998413,0.000102786,0.0001981426,0.0006324201,0.000277853,0.0003757677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004321335,0.0002687659,0.007809194,0.0002048117,0.00002117744,0.00002213027,0.001814567,0.000002137357,0.4989793,0.002951669,0.0007213501,0.4871617],"study_design_scores_gemma":[0.0006273533,0.0000567401,0.001744538,0.001169492,0.00008740993,0.0005447234,0.0004964093,0.9899863,0.002636662,0.0008520808,0.001594084,0.000204227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9197601,0.00004746659,0.006694973,0.06274237,0.0005780631,0.0007905166,0.000005431149,0.000104146,0.009276948],"genre_scores_gemma":[0.987343,0.001075636,0.01048412,0.0008585905,0.00007312994,0.0000125225,5.611535e-7,0.00001626639,0.0001362043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9899842,"threshold_uncertainty_score":0.9980918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02840764304687707,"score_gpt":0.2926960535636101,"score_spread":0.264288410516733,"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."}}