{"id":"W2008472008","doi":"10.12688/f1000research.4431.1","title":"ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis","year":2014,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"National Institutes of Health; Genome Canada","keywords":"Computer science; Context (archaeology); Biological network; Suite; Biological pathway; Computational biology; Gene regulatory network; Data mining; Bioinformatics; Biology; Gene; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002303204,0.002657996,0.001452245,0.003459492,0.0009321386,0.001764381,0.003995922,0.002045252,0.1996136],"category_scores_gemma":[0.01070176,0.001639013,0.001586284,0.001686954,0.0007138372,0.002786113,0.003127312,0.003853509,0.07108068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033953,"about_ca_system_score_gemma":0.002325852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005016754,"about_ca_topic_score_gemma":0.01069043,"domain_scores_codex":[0.9989032,0.0001787308,0.00007190479,0.0001858894,0.0005544983,0.0001057264],"domain_scores_gemma":[0.9967846,0.001830451,0.0001948362,0.0003706831,0.0005124011,0.0003069978],"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":[0.0003409581,0.00004315486,0.0008380013,0.001263026,0.0001868741,0.0004569532,0.0001811937,0.001344163,0.006863181,0.004834766,0.9379816,0.0456662],"study_design_scores_gemma":[0.0009563286,0.00006180763,0.003886225,0.0005133228,0.00009701947,0.0008773479,0.0001028632,0.0271248,0.03832182,0.03084537,0.8969218,0.0002912488],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.003694575,0.0009269709,0.1780775,0.002429226,0.001311255,0.0008154831,0.199419,0.5899347,0.02339124],"genre_scores_gemma":[0.05499828,0.0021931,0.4057135,0.006197534,0.0006803171,0.008587149,0.2846692,0.1797462,0.05721468],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1996136,"threshold_uncertainty_score":0.6677738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04223566747485158,"score_gpt":0.3206499843734001,"score_spread":0.2784143168985485,"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."}}