{"id":"W1877439477","doi":"10.1002/0471250953.bi0813s23","title":"Exploring Biological Networks with Cytoscape Software","year":2008,"lang":"en","type":"article","venue":"Current Protocols in Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; Unilever","keywords":"Interconnectivity; Biological network; Context (archaeology); Computer science; Computational biology; Software; Gene regulatory network; Genomics; Bioinformatics; Data science; Biology; Gene; Gene expression; Artificial intelligence; Genome; Genetics","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":[0.003411303,0.001760307,0.001504914,0.007950113,0.001768594,0.002946597,0.003833235,0.001386626,0.05314186],"category_scores_gemma":[0.008433002,0.001710831,0.002403175,0.0042589,0.0006381256,0.002976841,0.002665789,0.00422256,0.01112871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008128812,"about_ca_system_score_gemma":0.002762036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003389888,"about_ca_topic_score_gemma":0.005789799,"domain_scores_codex":[0.99858,0.0003726985,0.0001368894,0.0003189333,0.0005105446,0.00008093866],"domain_scores_gemma":[0.9952403,0.003372048,0.000256429,0.0004419847,0.0004189282,0.0002703478],"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":[0.0005022324,0.0002529828,0.00278676,0.009973616,0.002098048,0.001483988,0.001634891,0.0690114,0.04207439,0.1164302,0.4007317,0.3530198],"study_design_scores_gemma":[0.0002919586,0.00009218798,0.002089703,0.0006421835,0.0004124248,0.001078475,0.0001762597,0.2168348,0.03626571,0.2158555,0.5259079,0.000352946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.006834713,0.001766516,0.7634694,0.001218561,0.0008163438,0.0006700319,0.03571521,0.1735836,0.01592567],"genre_scores_gemma":[0.03842321,0.002111581,0.9026845,0.0005957049,0.0003125713,0.002678229,0.03502298,0.01119271,0.006978505],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.05314186,"threshold_uncertainty_score":0.1777772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1234336037324784,"score_gpt":0.2955983794445602,"score_spread":0.1721647757120818,"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."}}