{"id":"W2482079801","doi":"10.1158/1538-7445.am2016-5277","title":"Abstract 5277: The cBioPortal for cancer genomics and its application in precision oncology","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Documentation; Software; Pipeline (software); Computer science; Data science; Timeline; Genomics; Visualization; Medicine; Data mining; Genome; Biology; Geography","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":[0.000631793,0.00007983755,0.00009980773,0.00004711836,0.00009903837,0.00001660539,0.0002018731,0.0001282813,0.00002300098],"category_scores_gemma":[0.000165879,0.00005171284,0.00003066725,0.00007603577,0.000109252,0.000003621583,0.0001328258,0.00009759449,0.000004611431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001976524,"about_ca_system_score_gemma":0.000490876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004598167,"about_ca_topic_score_gemma":0.0044596,"domain_scores_codex":[0.9990731,0.00002403759,0.0001652637,0.0003308206,0.000110006,0.0002967599],"domain_scores_gemma":[0.9992946,0.0001860864,0.00005015266,0.0002192035,0.0001816029,0.0000683656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002438577,0.00002506671,0.001606292,0.0000177654,0.00001283341,6.517474e-7,0.00004987924,0.00003092724,0.8166535,0.0003512482,0.001831868,0.1791761],"study_design_scores_gemma":[0.001350727,0.0002633689,0.01333977,0.00005136974,0.000007936427,0.000002630905,0.00007929412,0.0001153135,0.3976481,0.00149487,0.5854737,0.0001729982],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864365,0.00902557,0.0003093725,0.002935031,0.0001306361,0.000783573,0.0001753744,0.000002577072,0.0002013273],"genre_scores_gemma":[0.9710847,0.02673653,0.00003403829,0.0001362529,0.0004416794,0.001239169,0.00001336879,0.00001901156,0.0002952673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5836418,"threshold_uncertainty_score":0.2488561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05432641164424332,"score_gpt":0.4170814731038963,"score_spread":0.362755061459653,"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."}}