{"id":"W4250917173","doi":"10.1158/1538-7445.am2015-2988","title":"Abstract 2988: International cancer genome consortium (ICGC)","year":2015,"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":"Globe; Genome; Library science; Identification (biology); Coding (social sciences); Biology; Computational biology; Genetics; Computer science; Sociology; Gene; Social science","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":[0.03465497,0.001857044,0.003077439,0.01072021,0.002930749,0.008636014,0.008144549,0.004451838,0.09436068],"category_scores_gemma":[0.07187518,0.001447957,0.001503855,0.03028995,0.001453416,0.002852042,0.00792955,0.005640614,0.04630245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01122398,"about_ca_system_score_gemma":0.06715094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1903635,"about_ca_topic_score_gemma":0.1427963,"domain_scores_codex":[0.9781539,0.005046156,0.002017591,0.003513511,0.008323478,0.002945275],"domain_scores_gemma":[0.8918393,0.009985039,0.003493318,0.01780793,0.06056745,0.01630705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001149079,0.00001910287,0.0007240415,0.0002574592,0.00002859158,0.00001712141,0.00004690917,0.0001109849,0.0001104529,0.001506851,0.9878381,0.009225462],"study_design_scores_gemma":[0.000191379,0.00002699174,0.00744482,0.0004193191,0.00004824637,0.00003616292,0.00006657212,0.0001377383,0.0002581695,0.0009942774,0.9903367,0.00003960456],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0009086533,0.001418258,0.002504545,0.01596448,0.003846077,0.001676555,0.9241534,0.002148077,0.04737991],"genre_scores_gemma":[0.002734348,0.0009123809,0.005043655,0.004026953,0.0006217045,0.003153564,0.9659883,0.001218338,0.01630073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1903635,"threshold_uncertainty_score":0.378511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1052717813936293,"score_gpt":0.4164946349609124,"score_spread":0.3112228535672831,"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."}}