{"id":"W2273114408","doi":"10.4236/act.2015.44008","title":"Comparison of CT Dose Reduction Algorithms in a Porcine Model","year":2015,"lang":"en","type":"article","venue":"Advances in Computed Tomography","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"CancerCare Manitoba; University of Manitoba","funders":"","keywords":"Medicine; Image quality; Iterative reconstruction; Algorithm; Image noise; Nuclear medicine; Noise (video); Abdominal computed tomography; Radiology; Mathematics; Artificial intelligence; Computer science; 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":[0.0002000923,0.0001161288,0.0003732027,0.0007767642,0.0000130495,0.000006056829,0.00008491409,0.00002872694,0.000003010178],"category_scores_gemma":[0.00002757694,0.000112649,0.00006331806,0.001368896,0.00006994212,0.0003647618,0.00002277371,0.0001937889,0.000001648445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004547739,"about_ca_system_score_gemma":0.00006055376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000452458,"about_ca_topic_score_gemma":0.00001312828,"domain_scores_codex":[0.9988753,0.00003519896,0.0004488984,0.0002250279,0.0002378873,0.0001776657],"domain_scores_gemma":[0.9994636,0.00002748661,0.000136515,0.0002007026,0.00008091982,0.00009077055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002250145,0.0007749041,0.5373389,0.00008082883,0.00002604249,0.00002858763,0.001340452,0.2879401,0.000566252,0.0002993528,0.0006193856,0.1707603],"study_design_scores_gemma":[0.003723447,0.0002450662,0.03400208,0.0002518461,0.0000200479,0.00003982164,0.0004792855,0.9536669,0.003517385,0.002199903,0.001696958,0.0001573198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530559,0.01633783,0.02545208,0.000557325,0.0005361892,0.0004734511,0.000004728735,0.00009195915,0.003490496],"genre_scores_gemma":[0.9757498,0.0001838941,0.02386181,0.00006606038,0.00007496174,0.0000103792,0.00002776063,0.00001117684,0.0000141832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6657268,"threshold_uncertainty_score":0.4593694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0394839395391751,"score_gpt":0.3675984480771606,"score_spread":0.3281145085379855,"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."}}