{"id":"W2997760522","doi":"10.1007/s10637-020-00892-8","title":"Patient selection for a developmental therapeutics program using whole genome and Transcriptome analysis","year":2020,"lang":"en","type":"article","venue":"Investigational New Drugs","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency","funders":"","keywords":"Clinical trial; Transcriptome; Medicine; Genome; Precision medicine; Oncology; Bioinformatics; Selection (genetic algorithm); Internal medicine; Gene; Computational biology; Gene expression; Biology; Pathology; Genetics; Computer science","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":[0.001114283,0.000387504,0.0006119637,0.001048302,0.0006186465,0.0009679224,0.0003205255,0.0005826551,0.007820593],"category_scores_gemma":[0.002204683,0.0001367171,0.0006413002,0.0006483893,0.0001743926,0.0002773545,0.0005168521,0.0006809738,0.002110745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005158797,"about_ca_system_score_gemma":0.001576058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001114581,"about_ca_topic_score_gemma":0.001402381,"domain_scores_codex":[0.9995317,0.0001136753,0.00005519074,0.00008928881,0.0001246408,0.00008555367],"domain_scores_gemma":[0.9990698,0.0002716848,0.00009837079,0.00007493969,0.0002190237,0.000266243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006823262,0.002077698,0.4352272,0.0004744566,0.0002197156,0.01651303,0.0006016593,0.002712345,0.1109781,0.003183552,0.04601678,0.3751722],"study_design_scores_gemma":[0.001124981,0.008383555,0.6118807,0.0005743645,0.001201774,0.03577883,0.001715447,0.01778426,0.1118546,0.006500444,0.2029871,0.000213951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8756674,0.003234317,0.05653948,0.008390595,0.0005500832,0.005501186,0.008805721,0.0009472352,0.04036395],"genre_scores_gemma":[0.8940604,0.002429644,0.07034706,0.006883489,0.0005061372,0.003721202,0.01060531,0.0004865487,0.01096024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007820593,"threshold_uncertainty_score":0.02616251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02847075282832528,"score_gpt":0.2639221654190349,"score_spread":0.2354514125907096,"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."}}