{"id":"W2011474181","doi":"10.1038/nature12831","title":"Inconsistency in large pharmacogenomic studies","year":2013,"lang":"en","type":"article","venue":"Nature","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":534,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Université de Montréal; Montreal Clinical Research Institute; Princess Margaret Cancer Centre","funders":"National Cancer Institute","keywords":"Pharmacogenomics; Computational biology; Biology; Bioinformatics","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":[0.0001162641,0.00009714852,0.0001044084,0.00003011514,0.00003486501,0.00001340882,0.0001267054,0.0005358778,0.00004688548],"category_scores_gemma":[0.0000253804,0.00008180494,0.00004448035,0.00005898278,0.00002466489,0.000003685475,0.0001121015,0.0005321358,0.00006096042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001357775,"about_ca_system_score_gemma":0.00002482718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004178714,"about_ca_topic_score_gemma":0.00003578428,"domain_scores_codex":[0.9994402,0.00001566057,0.0001512154,0.0001380433,0.00004969181,0.0002051833],"domain_scores_gemma":[0.9997016,0.000006528826,0.00004067732,0.0001586737,0.00005471905,0.00003779098],"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":[0.00009597561,0.0002754581,0.0280532,0.0001743323,0.0005314267,0.00001753767,0.001226939,0.0001650184,0.3830801,0.002111297,0.5465913,0.03767732],"study_design_scores_gemma":[0.007765139,0.000447657,0.04085242,0.0001399949,0.00008154214,0.00009096994,0.003738219,0.003964733,0.0567413,0.01316286,0.8711343,0.001880835],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978682,0.01727102,0.00003641268,0.0005881527,0.0003508981,0.0002158041,0.00001391389,0.000007649642,0.002834124],"genre_scores_gemma":[0.9952436,0.0006799125,0.0004224237,0.002853206,0.0001963014,0.00002278561,0.00004639588,0.000009201883,0.0005261448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3263388,"threshold_uncertainty_score":0.413318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007214287074636669,"score_gpt":0.2729861886712832,"score_spread":0.2657719015966465,"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."}}