{"id":"W2138980743","doi":"10.1109/tmi.2004.839680","title":"Computational engine for development of complex cascaded models of signal and noise in X-ray imaging systems","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Detective quantum efficiency; Computer science; Noise (video); Metric (unit); Computational complexity theory; SIGNAL (programming language); Algorithm; Monte Carlo method; Image quality; Theoretical computer science; Artificial intelligence; Image (mathematics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007351853,0.0007113608,0.0007920759,0.0005260497,0.0006540006,0.0008194783,0.001493373,0.0008459541,0.004526006],"category_scores_gemma":[0.00188703,0.0004825023,0.0009796843,0.0003907625,0.0005414718,0.0009011165,0.0008384634,0.000878627,0.000662316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008356897,"about_ca_system_score_gemma":0.001324698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004982279,"about_ca_topic_score_gemma":0.005013611,"domain_scores_codex":[0.999788,0.00004868006,0.00001631919,0.00003218986,0.0000924694,0.00002229137],"domain_scores_gemma":[0.9994721,0.000338387,0.00003695737,0.00005001124,0.00008269098,0.00001991344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001926285,0.00002293873,0.0002608826,0.000045299,0.00001150817,0.00006804337,0.00005382417,0.9671836,0.002233435,0.0217134,0.0002520133,0.008135885],"study_design_scores_gemma":[0.00000246002,0.000002972313,0.00001189395,0.000001218449,0.000001453924,0.000003327439,0.000001591746,0.9979893,0.0003566143,0.001429881,0.0001978766,0.000001385315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01176184,0.00003423154,0.9857177,0.00005008271,0.00000952849,0.00004998337,0.00005643622,0.0005244573,0.001795897],"genre_scores_gemma":[0.2789067,0.0001799611,0.7157897,0.00004227474,0.00001466308,0.0005618106,0.0002188898,0.0002521769,0.004033872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004982279,"threshold_uncertainty_score":0.01514107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154702600232731,"score_gpt":0.2782842022227957,"score_spread":0.2567371762204684,"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."}}