{"id":"W4386215906","doi":"10.32920/24043230","title":"A Bladder Cancer Grading System Using Deep Neural Network Architectures","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Grading (engineering); Computer science; Artificial intelligence; Bladder cancer; Artificial neural network; Medicine; Cancer; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000523075,0.0008618146,0.0005852277,0.001808255,0.000507408,0.001039,0.001214315,0.0009173375,0.003938335],"category_scores_gemma":[0.001123991,0.0003894141,0.0007853497,0.0007557228,0.0001637377,0.000785047,0.001367719,0.0009036617,0.001827532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076685,"about_ca_system_score_gemma":0.001260191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01193067,"about_ca_topic_score_gemma":0.01585342,"domain_scores_codex":[0.9995952,0.00004487688,0.00004566923,0.0001195875,0.0001350159,0.00005969401],"domain_scores_gemma":[0.9996248,0.00003660541,0.00003560005,0.00003678908,0.0002214172,0.00004472197],"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":[0.000552897,0.0002616717,0.01591048,0.000443686,0.0001626213,0.0005627024,0.0001125319,0.06704649,0.02175314,0.00208274,0.04465713,0.8464539],"study_design_scores_gemma":[0.00004841309,0.0002609429,0.0086965,0.0001267322,0.00008751252,0.0003979416,0.00007665089,0.9478582,0.02268229,0.003767353,0.01591214,0.00008539892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1093365,0.002067905,0.8370259,0.001514464,0.0005731549,0.00111687,0.008072188,0.02642061,0.01387236],"genre_scores_gemma":[0.5483276,0.001290933,0.4099046,0.0007649008,0.0001760918,0.0008772977,0.01929715,0.0006160754,0.01874523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01193067,"threshold_uncertainty_score":0.02372247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06762018724936457,"score_gpt":0.3268894794050994,"score_spread":0.2592692921557349,"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."}}