{"id":"W4225613061","doi":"10.2139/ssrn.4049605","title":"Gan Quality Metrics for Evaluating Computed Tomography Image Generators","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nova Scotia Health Authority","funders":"","keywords":"Computed tomography; Image quality; Quality (philosophy); Tomography; Computer science; Image (mathematics); Artificial intelligence; Computer vision; Medicine; Radiology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004913664,0.001172328,0.0008629108,0.003689973,0.0002508572,0.002135884,0.001155854,0.001092458,0.002746258],"category_scores_gemma":[0.01964312,0.0002795916,0.0005994844,0.001735052,0.0005304412,0.001072634,0.0009384508,0.0006769742,0.0005476961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009836119,"about_ca_system_score_gemma":0.0006610784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486447,"about_ca_topic_score_gemma":0.003084012,"domain_scores_codex":[0.9973906,0.0007087516,0.0002393149,0.0002210141,0.001345545,0.00009473888],"domain_scores_gemma":[0.9869423,0.007298947,0.000968823,0.0007168727,0.00371708,0.0003558629],"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":[0.002903696,0.0003293081,0.04173282,0.001242104,0.000658849,0.0004115806,0.0002466755,0.3288268,0.04326931,0.007402265,0.009534796,0.5634417],"study_design_scores_gemma":[0.00007551935,0.0006213193,0.01296652,0.0001001448,0.000155536,0.0009832405,0.00009004292,0.9555988,0.0245291,0.002411147,0.002406867,0.00006167537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1207284,0.004348182,0.8628916,0.0002756301,0.0001895988,0.0004889207,0.002161901,0.004207949,0.004707754],"genre_scores_gemma":[0.7100487,0.00141306,0.2805018,0.0001844155,0.0001052913,0.0002257156,0.004691768,0.000967738,0.001861599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004913664,"threshold_uncertainty_score":0.02598619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04560500893150145,"score_gpt":0.3946220798411491,"score_spread":0.3490170709096476,"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."}}