{"id":"W3191863614","doi":"10.1101/2021.08.06.455345","title":"Immunohistochemical assays for bladder cancer molecular subtyping: Optimizing parsimony and performance using Lund taxonomy","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bladder and Urothelial Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Ontario Institute for Cancer Research; Government of Ontario; Bladder Cancer Canada; Cancer Research Society","keywords":"Subtyping; Immunohistochemistry; Bladder cancer; Decision tree; Pathology; Computational biology; Biology; Computer science; Medicine; Internal medicine; Artificial intelligence; Cancer","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009633565,0.001368356,0.001398626,0.002693223,0.001182253,0.001970942,0.001277429,0.001222494,0.0009739153],"category_scores_gemma":[0.01771656,0.0004979159,0.001594402,0.001588495,0.0006812123,0.001599719,0.001914719,0.001725079,0.0006713098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798694,"about_ca_system_score_gemma":0.002905994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007518547,"about_ca_topic_score_gemma":0.008049729,"domain_scores_codex":[0.9964638,0.00178873,0.0003733097,0.000570609,0.0005178485,0.0002857587],"domain_scores_gemma":[0.9906672,0.005942335,0.0009392645,0.0008160332,0.001378302,0.0002568923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001677227,0.0004274179,0.1647727,0.0002594783,0.000696155,0.0002493126,0.0005144587,0.4899322,0.01481572,0.006716174,0.0047384,0.3152008],"study_design_scores_gemma":[0.00003773221,0.0001374256,0.005685904,0.00004108351,0.00006444644,0.00007083351,0.00008243234,0.9852942,0.002839769,0.005073676,0.0006522804,0.00002022927],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5489355,0.0009816757,0.4446624,0.0006981926,0.00006459323,0.0003723942,0.0009488321,0.001298667,0.00203777],"genre_scores_gemma":[0.7432462,0.0002101734,0.2534817,0.0001599889,0.00003969411,0.0002802858,0.001532934,0.0001529578,0.0008960648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009633565,"threshold_uncertainty_score":0.05094779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03294029652403457,"score_gpt":0.26475549264315,"score_spread":0.2318151961191154,"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."}}