{"id":"W4303700015","doi":"10.3390/cancers14194911","title":"Development of a Clinically Applicable NanoString-Based Gene Expression Classifier for Muscle-Invasive Bladder Cancer Molecular Stratification","year":2022,"lang":"en","type":"article","venue":"Cancers","topic":"Bladder and Urothelial Cancer Treatments","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"McMaster University","keywords":"Concordance; Immunohistochemistry; Bladder cancer; Gene expression; Classifier (UML); Molecular diagnostics; Oncology; Internal medicine; Medicine; Gene; Pathology; Bioinformatics; Biology; Cancer; Computer science; Artificial intelligence","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":[0.0006451842,0.0003463462,0.0004422472,0.0006157465,0.0001774407,0.0004432062,0.0003474917,0.0003615056,0.0007579669],"category_scores_gemma":[0.001105521,0.0001202634,0.000253223,0.0002962798,0.0001277776,0.0002142582,0.0003470411,0.0003500144,0.0003711458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003256798,"about_ca_system_score_gemma":0.0005173102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001206479,"about_ca_topic_score_gemma":0.001970584,"domain_scores_codex":[0.9997253,0.00004714978,0.00002400086,0.00008262868,0.00008451462,0.00003641903],"domain_scores_gemma":[0.9997441,0.00008659773,0.00004235953,0.00002145268,0.00008280765,0.00002265822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001617873,0.0005037347,0.202437,0.0003387217,0.0003610003,0.0005066256,0.000136119,0.03640112,0.4204908,0.001003375,0.008959099,0.3272444],"study_design_scores_gemma":[0.0001599698,0.0008316138,0.1289163,0.00005913647,0.0003069366,0.001063079,0.0001710374,0.6786953,0.1768855,0.001749182,0.01108403,0.00007797845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.899969,0.0008395014,0.09159406,0.0003157015,0.00007562924,0.0003490743,0.004169426,0.0008605328,0.001827177],"genre_scores_gemma":[0.9078318,0.0002541395,0.08302075,0.0002184694,0.00004364323,0.0004202858,0.006788075,0.00004333202,0.001379524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001206479,"threshold_uncertainty_score":0.003412127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04339852554200791,"score_gpt":0.3263791572930009,"score_spread":0.282980631750993,"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."}}