{"id":"W2981350712","doi":"10.1093/nar/gkz946","title":"Pathway Commons 2019 Update: integration, analysis and exploration of pathway data","year":2019,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":331,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; National Human Genome Research Institute; Defense Advanced Research Projects Agency; National Institutes of Health","keywords":"Biology; Computational biology; Data integration; Genetics; Evolutionary biology; Data science; Bioinformatics; Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001165915,0.00009942747,0.0001828209,0.0001634676,0.00008427374,0.00005697662,0.0004827768,0.0001589617,0.00009055356],"category_scores_gemma":[0.00006246767,0.00008551677,0.00004695123,0.0004275694,0.0001353524,0.0000329398,0.0006426365,0.0001998808,0.00005502688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001026322,"about_ca_system_score_gemma":0.0001024283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005904954,"about_ca_topic_score_gemma":0.0002100405,"domain_scores_codex":[0.9987936,0.0001199144,0.0002786853,0.0003042381,0.0002695306,0.0002340503],"domain_scores_gemma":[0.9984686,0.00003025594,0.00007913185,0.001113052,0.0002321335,0.00007679159],"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":[0.0003622603,0.0002569455,0.02689039,0.0001342207,0.001083564,0.000002519514,0.001084966,0.0002419838,0.6823597,0.008805703,0.04356385,0.2352139],"study_design_scores_gemma":[0.003712059,0.002484074,0.03384778,0.0001337979,0.0002880721,0.00001645941,0.005337251,0.1525021,0.2763563,0.006293162,0.5175631,0.001465813],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965627,0.0007131065,0.02765312,0.0006152222,0.00009681995,0.0004617018,0.0003902834,0.00001040341,0.004432357],"genre_scores_gemma":[0.994785,0.0004305862,0.001631193,0.0000499073,0.00006783066,0.000006423316,0.0022282,0.0000130855,0.0007877589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4739993,"threshold_uncertainty_score":0.3487273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04507245269159469,"score_gpt":0.3184225766611605,"score_spread":0.2733501239695658,"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."}}