{"id":"W4224289048","doi":"10.1093/bioinformatics/btac286","title":"Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Ferroptosis and cancer prognosis","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Princess Margaret Cancer Centre; CancerCare Manitoba; Public Health Ontario; University of Toronto","funders":"","keywords":"Computer science; Data mining; Concordance; Machine learning; Artificial intelligence; Bioinformatics; 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":[0.0002960781,0.0001533849,0.0002555179,0.0001633112,0.0002037907,0.00002434555,0.0001168395,0.0000566843,0.0003565795],"category_scores_gemma":[0.000062914,0.0001324496,0.000144901,0.0002496628,0.00002150479,0.00007508328,0.00005419608,0.0001473627,0.00008279584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003325295,"about_ca_system_score_gemma":0.0002414674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008278536,"about_ca_topic_score_gemma":0.00000323838,"domain_scores_codex":[0.9987907,0.00001707548,0.000447894,0.0001349589,0.0003552077,0.0002541995],"domain_scores_gemma":[0.9992673,0.00003846264,0.0001177945,0.0002449624,0.0001775915,0.0001538943],"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":[0.004928485,0.002062328,0.004331305,0.001365837,0.0005488522,0.000004861847,0.00658937,0.6667689,0.005356167,0.0004691482,0.1670136,0.1405611],"study_design_scores_gemma":[0.001866986,0.0007159947,0.0002608223,0.0000295616,0.0001024139,0.000003642656,0.0003805446,0.9658479,0.0006005655,0.00001160524,0.03004199,0.0001379409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08707419,0.00006164591,0.9010156,0.002772623,0.0006903283,0.003642392,0.002120779,0.0004296943,0.002192681],"genre_scores_gemma":[0.7551969,0.00001598869,0.22508,0.00678308,0.0002577447,0.002355392,0.003293595,0.000122683,0.006894696],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6759357,"threshold_uncertainty_score":0.5401139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521290491139316,"score_gpt":0.2645198459108921,"score_spread":0.2393069409994989,"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."}}