{"id":"W7115703867","doi":"10.1097/js9.0000000000004403","title":"TB-MIL: deep learning-based identification of TMB status in bladder cancer from histopathological images","year":2025,"lang":"en","type":"article","venue":"International Journal of Surgery","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"","keywords":"Bladder cancer; Deep learning; Immunotherapy; Cancer; Metastasis; Pathological; Deep sequencing; Identification (biology)","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":[0.001105607,0.0008961748,0.0005075678,0.00152884,0.0002664332,0.0008775398,0.001345127,0.000873535,0.0014847],"category_scores_gemma":[0.002492098,0.0003742126,0.0007567951,0.0005362207,0.0002954085,0.0006837542,0.001081603,0.00118013,0.0008021478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000848122,"about_ca_system_score_gemma":0.0008392148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005498286,"about_ca_topic_score_gemma":0.006778019,"domain_scores_codex":[0.9997345,0.00005621494,0.00002424757,0.0000884575,0.0000497872,0.00004683123],"domain_scores_gemma":[0.9994333,0.0002326901,0.00009533093,0.00005341805,0.0001324541,0.00005267964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008920776,0.0006929866,0.06999225,0.0004693333,0.000516402,0.0004462592,0.0001570987,0.3324298,0.01905864,0.001204971,0.01837298,0.5557673],"study_design_scores_gemma":[0.0000141374,0.00007602882,0.002819963,0.00003232936,0.00003802861,0.00007153584,0.00001820354,0.9915879,0.003784406,0.0008194049,0.0007259321,0.00001214362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4170531,0.003954898,0.5504392,0.001639312,0.0003170843,0.00037073,0.005520388,0.01651153,0.004193779],"genre_scores_gemma":[0.884691,0.0005091756,0.1055574,0.0004257099,0.00008353134,0.0002413766,0.005224716,0.0001498907,0.00311722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005498286,"threshold_uncertainty_score":0.01093256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224104035943172,"score_gpt":0.3229329389516773,"score_spread":0.3006918985922456,"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."}}