{"id":"W4235059002","doi":"10.1158/1538-7445.am2013-2004","title":"Abstract 2004: International Cancer Genome Consortium (ICGC).","year":2013,"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":"Ontario Institute for Cancer Research","funders":"","keywords":"Genome; Biology; Computational biology; Library science; Genetics; Computer science; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006721216,0.002533707,0.003411378,0.01069772,0.001530825,0.006682037,0.005516408,0.003204743,0.1751683],"category_scores_gemma":[0.02197935,0.001721107,0.001316973,0.04343323,0.0009846915,0.002600196,0.003493981,0.006100441,0.1227014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008965863,"about_ca_system_score_gemma":0.02137725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1752093,"about_ca_topic_score_gemma":0.1115879,"domain_scores_codex":[0.9932673,0.001284682,0.000835576,0.001619317,0.002291711,0.0007013521],"domain_scores_gemma":[0.9769891,0.002729128,0.001647545,0.003975864,0.0117847,0.002873698],"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":[0.00006576889,0.00001606652,0.0003790587,0.0002355684,0.00002490528,0.00001227636,0.00002172884,0.00008349533,0.00004651929,0.0005403993,0.9855802,0.01299406],"study_design_scores_gemma":[0.00009160806,0.00001873457,0.006537026,0.0004205229,0.00003290435,0.00003452763,0.00006132072,0.00009770376,0.0001402813,0.0008748863,0.9916632,0.00002722334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002194122,0.001878081,0.0005329574,0.003680286,0.001007736,0.0002676287,0.9660204,0.00137685,0.02501666],"genre_scores_gemma":[0.001443203,0.001810531,0.002096147,0.001471746,0.000204713,0.0009989905,0.9671009,0.000746225,0.02412757],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1752093,"threshold_uncertainty_score":0.5859963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04574030055709758,"score_gpt":0.3770965824445834,"score_spread":0.3313562818874858,"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."}}