{"id":"W1971413206","doi":"10.1109/nssmic.2011.6153881","title":"Impact of erroneous kinetic model formulation in Direct 4D image reconstruction","year":2011,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council","keywords":"Parametric statistics; Iterative reconstruction; Computer science; Image (mathematics); Artificial intelligence; Algorithm; Physics; Mathematics; Statistics","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":[0.00008473972,0.00005789255,0.0001367955,0.00009126445,0.00001152206,0.000002290446,0.00003291696,0.00004266009,0.0003818785],"category_scores_gemma":[0.00004018149,0.00004273338,0.00005864662,0.0001175331,0.00005029713,0.00005457769,0.00001121208,0.0000748047,0.000003964236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004501038,"about_ca_system_score_gemma":0.00004710025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007438911,"about_ca_topic_score_gemma":0.00001215446,"domain_scores_codex":[0.9995158,0.000006840819,0.0002039807,0.0001037954,0.0000750873,0.00009446849],"domain_scores_gemma":[0.9996572,0.00001106424,0.00004913365,0.0001752121,0.00004887236,0.00005856841],"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":[0.0005205923,0.001910301,0.1906183,0.000248248,0.0001024345,0.00002148231,0.001524024,0.0003231709,0.6147277,0.01743044,0.005552463,0.1670209],"study_design_scores_gemma":[0.000690215,0.0002603556,0.08525433,0.0001034989,0.00004290344,0.00009291378,0.00001824731,0.8812235,0.02463112,0.007565098,0.00001251836,0.0001052811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8860498,0.000005908486,0.06945068,0.000106835,0.000008224118,0.0002609756,0.000002406817,0.00008200585,0.04403318],"genre_scores_gemma":[0.8172337,0.00001327698,0.1825411,0.00002085225,0.000008671528,0.00001602053,0.000006327613,0.000006256628,0.0001538192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8809004,"threshold_uncertainty_score":0.4181302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04358882159173999,"score_gpt":0.3350085868994229,"score_spread":0.2914197653076829,"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."}}