{"id":"W2915953284","doi":"10.5281/zenodo.1042581","title":"ICGC-TCGA-PanCancer/CGP-Somatic-Docker: 2.0.2","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research; Ontario Institute for Cancer Research","funders":"","keywords":"Somatic cell; Computer science; Biology; Genetics; Gene","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":[0.002155678,0.004759724,0.002886652,0.004628066,0.001795139,0.004239306,0.004176743,0.002411558,0.2746906],"category_scores_gemma":[0.005239411,0.003084622,0.002510612,0.003309892,0.00050538,0.002274495,0.00331827,0.003325404,0.2237381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115291,"about_ca_system_score_gemma":0.001566822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004654752,"about_ca_topic_score_gemma":0.00410853,"domain_scores_codex":[0.9986801,0.0001411084,0.0001219134,0.0004961267,0.0003483906,0.0002124406],"domain_scores_gemma":[0.9976187,0.0008409816,0.0001529182,0.0007405754,0.0003738889,0.0002729048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001601736,0.0001232872,0.003060505,0.001556266,0.0002404523,0.0002642403,0.0001753033,0.001179812,0.01052577,0.00115075,0.9521775,0.02794443],"study_design_scores_gemma":[0.001079623,0.0001898572,0.009551951,0.0003280056,0.0002652528,0.0007338157,0.0001442847,0.01002475,0.06674534,0.004911982,0.9057221,0.0003031525],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.003076468,0.0002978533,0.02235471,0.0004061693,0.0004075978,0.0002554076,0.6205149,0.3395323,0.01315448],"genre_scores_gemma":[0.01172733,0.0002554782,0.03113772,0.000332162,0.00008653493,0.0008312777,0.7953254,0.1503625,0.009941576],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2746906,"threshold_uncertainty_score":0.9189315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706756337695836,"score_gpt":0.2321777221478389,"score_spread":0.2151101587708806,"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."}}