{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005223088,0.00007490699,0.000263418,0.0004798897,0.00001329618,0.00001590594,0.0001028428,0.00005933234,0.0004935767],"category_scores_gemma":[0.0003718979,0.00006215314,0.0002001061,0.0001614383,0.00008193941,0.00008887421,0.00001287049,0.000202921,0.000001685605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003002305,"about_ca_system_score_gemma":0.0003537504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004075442,"about_ca_topic_score_gemma":0.00004026674,"domain_scores_codex":[0.9986386,0.00007358171,0.0007274551,0.0001027839,0.0003589434,0.00009868836],"domain_scores_gemma":[0.9985876,0.0003721998,0.0004842192,0.00007066153,0.000453185,0.00003213357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004218124,0.0002996326,0.7882258,0.00002075651,0.0003232273,0.0002132833,0.0001255806,0.0004741784,0.1260492,0.00001052056,0.002053685,0.07798604],"study_design_scores_gemma":[0.001313188,0.0000325906,0.9610865,0.0003992108,0.00004728324,0.00001398478,0.0001059997,0.0002603153,0.03072753,0.0001116723,0.005845091,0.00005660863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889035,0.005153947,0.00155001,0.002710012,0.001446871,0.00004832477,0.00002105807,0.000006608589,0.0001596359],"genre_scores_gemma":[0.9973441,0.001661619,0.000108659,0.0004577228,0.0001268588,0.00000431417,0.00002112864,0.000005961383,0.0002696289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1728607,"threshold_uncertainty_score":0.5404319,"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."}}