{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005231447,0.00163276,0.001506309,0.008205804,0.001167501,0.004770203,0.004268145,0.001954352,0.05940711],"category_scores_gemma":[0.01728187,0.00125983,0.00184406,0.008438434,0.0005865478,0.002926853,0.006669611,0.003210156,0.04741603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001430321,"about_ca_system_score_gemma":0.003905944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006223899,"about_ca_topic_score_gemma":0.005327263,"domain_scores_codex":[0.9974318,0.0007279762,0.0003068145,0.0003896479,0.0009495678,0.0001941763],"domain_scores_gemma":[0.9921494,0.002935773,0.0004599199,0.001862554,0.001589608,0.001002795],"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":[0.000289836,0.00004578172,0.001540244,0.00127805,0.000106506,0.0002040801,0.0001560159,0.002190599,0.002110284,0.007333225,0.9191714,0.06557393],"study_design_scores_gemma":[0.0004576985,0.00006616311,0.005081225,0.0009836038,0.0001798923,0.0007052561,0.00009026227,0.02060594,0.005997596,0.0294573,0.9362103,0.0001647377],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.004778403,0.005259446,0.2269319,0.005417626,0.001548507,0.001076533,0.3735775,0.3467502,0.03466],"genre_scores_gemma":[0.02767472,0.003351111,0.2223602,0.00230101,0.0007031171,0.002824594,0.6634818,0.06645781,0.0108456],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05940711,"threshold_uncertainty_score":0.1987366,"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."}}