{"id":"W2153167299","doi":"10.1093/bioinformatics/btr035","title":"OrthoNets: simultaneous visual analysis of orthologs and their interaction neighborhoods across different organisms","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Identification (biology); Plug-in; Organism; Computer science; Protein–protein interaction; Computational biology; Model organism; Protein Interaction Networks; Biology; Genetics; Programming language; Gene; Ecology","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":[0.0005700231,0.0008227513,0.0006561836,0.003054748,0.0005600469,0.001277931,0.0009953154,0.0004609052,0.02001008],"category_scores_gemma":[0.002052081,0.0004021583,0.0007861961,0.001650619,0.000279957,0.001949981,0.002259084,0.0006942876,0.002634648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002406096,"about_ca_system_score_gemma":0.0005391049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002153832,"about_ca_topic_score_gemma":0.003855512,"domain_scores_codex":[0.9997267,0.00004045281,0.00001796158,0.0000863144,0.000097549,0.00003091195],"domain_scores_gemma":[0.9991283,0.0003631911,0.0001030484,0.0001512342,0.0001110145,0.0001432302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003739887,0.0003313233,0.02540735,0.005017562,0.001060994,0.002594509,0.001929711,0.01768489,0.3476373,0.02188759,0.2337244,0.3389845],"study_design_scores_gemma":[0.0006804045,0.0005085658,0.1005889,0.0006658357,0.0006149994,0.005049371,0.001441175,0.2779246,0.1653213,0.0743968,0.3722472,0.0005608626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2404676,0.001780632,0.4451401,0.001005121,0.0005549965,0.000467341,0.101907,0.1884611,0.02021608],"genre_scores_gemma":[0.4881539,0.001365539,0.3927111,0.000260959,0.00012532,0.0007278318,0.09243309,0.01427284,0.009949367],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02001008,"threshold_uncertainty_score":0.06694043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239312957601071,"score_gpt":0.2534325284217612,"score_spread":0.2410393988457505,"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."}}