{"id":"W4282916472","doi":"10.1158/1538-7445.am2022-5176","title":"Abstract 5176: Tumor dynamic model-based decision support for phase Ib immunotherapy combination studies","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Roche (Canada)","funders":"","keywords":"Medicine; Hazard ratio; Bevacizumab; Internal medicine; Carboplatin; Oncology; Clinical endpoint; Proportional hazards model; Cancer; Confidence interval; Urology; Nuclear medicine; Chemotherapy; Clinical trial","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":[0.007862957,0.001449401,0.001751621,0.001050208,0.0004348833,0.002415201,0.001257856,0.001440089,0.009754842],"category_scores_gemma":[0.02302854,0.0007412501,0.001262089,0.0006550545,0.0004482152,0.001084323,0.001441703,0.002665198,0.001236409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001359819,"about_ca_system_score_gemma":0.002560874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005023795,"about_ca_topic_score_gemma":0.00502539,"domain_scores_codex":[0.997242,0.002038105,0.0001178346,0.0002918925,0.0002133111,0.00009691507],"domain_scores_gemma":[0.9840109,0.01359138,0.000833246,0.0002667507,0.0007833072,0.0005144386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001629783,0.0005091322,0.004274561,0.0004213699,0.000551703,0.0001854055,0.00007946792,0.8800848,0.0007096087,0.005813322,0.01156779,0.09417317],"study_design_scores_gemma":[0.0001682876,0.0001032984,0.0001893812,0.00005120556,0.00004807662,0.00001396864,0.00001029286,0.9904351,0.0001678823,0.007544931,0.001258675,0.000008925398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0858615,0.004683586,0.8741047,0.01122921,0.0005073498,0.001205484,0.004890454,0.004333665,0.01318398],"genre_scores_gemma":[0.7714998,0.001522072,0.2161457,0.002066169,0.0004722066,0.001594377,0.003822976,0.0003209579,0.002555848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009754842,"threshold_uncertainty_score":0.04158378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06388238886099472,"score_gpt":0.4513000233609258,"score_spread":0.3874176344999311,"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."}}