{"id":"W2727134083","doi":"10.1093/bioinformatics/btx441","title":"Reactome enhanced pathway visualization","year":2017,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":187,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"National Institutes of Health; National Human Genome Research Institute; University of Toronto; European Bioinformatics Institute","keywords":"Scalable Vector Graphics; Computer science; Visualization; Hierarchy; Scalability; World Wide Web; Information retrieval; Data mining; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002035042,0.0001513344,0.0001296106,0.00003205297,0.0003591724,0.0002030845,0.0004163872,0.0001788609,0.00001631523],"category_scores_gemma":[0.0000985856,0.000136797,0.00007507881,0.0000255703,0.00008697111,0.00001922307,0.0002155759,0.00006753767,0.00009790945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001216578,"about_ca_system_score_gemma":0.00006351279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006231347,"about_ca_topic_score_gemma":0.00001647716,"domain_scores_codex":[0.999155,0.000008208051,0.000343222,0.0001106016,0.00013327,0.000249712],"domain_scores_gemma":[0.9986296,0.000004560899,0.0003607975,0.0008310974,0.00008204234,0.00009185277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003042787,0.0002779814,0.002100413,0.0005503038,0.0004073265,0.000005669065,0.003460562,0.0003964896,0.2825944,0.02403255,0.03541339,0.6504566],"study_design_scores_gemma":[0.003354256,0.0008189541,0.007640689,0.0001437285,0.00005782585,0.00004986041,0.0008662701,0.05061041,0.379182,0.001906654,0.5536528,0.001716573],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3928504,0.0002590966,0.3877063,0.0002885965,0.001713128,0.0008064787,0.00009700341,0.0001028845,0.2161761],"genre_scores_gemma":[0.9920369,0.0001575225,0.005471567,0.000440642,0.0002989383,0.00001106746,0.0002368882,0.00001884335,0.001327675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6487401,"threshold_uncertainty_score":0.5578419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236784390598909,"score_gpt":0.2603399107743852,"score_spread":0.2479720668683962,"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."}}