{"id":"W3034400399","doi":"10.1101/2020.06.16.153817","title":"The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Discovery Centre; University Health Network","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; National Cancer Institute; Wellcome Trust; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; National Institute of Mental Health; National Eye Institute; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Institut Français de Bioinformatique; Associazione Italiana per la Ricerca sul Cancro; European Bioinformatics Institute","keywords":"Interactome; Coronaviridae; Coronavirus disease 2019 (COVID-19); Coronavirus; Computational biology; Biology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Proteomics; Disease; Genetics; Infectious disease (medical specialty); Medicine; Gene","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":[0.001000639,0.001016921,0.001075471,0.006659043,0.000817502,0.002275902,0.0008114181,0.0009343788,0.004151926],"category_scores_gemma":[0.003308672,0.0002931528,0.0008354561,0.008653312,0.0004305115,0.001542159,0.002324964,0.001120858,0.003031865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008752996,"about_ca_system_score_gemma":0.0009412653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002866532,"about_ca_topic_score_gemma":0.004581066,"domain_scores_codex":[0.9984483,0.0002601602,0.0001294713,0.0005589341,0.0004753759,0.0001277254],"domain_scores_gemma":[0.9978809,0.0007091112,0.0004077743,0.0004361004,0.0003036153,0.000262568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002307948,0.0002998742,0.148029,0.01670318,0.001852726,0.00292398,0.001728549,0.009878579,0.1063288,0.02120166,0.5468401,0.1419056],"study_design_scores_gemma":[0.0001109088,0.0001375192,0.2294398,0.001628428,0.0005248162,0.002579111,0.0009035073,0.01402489,0.01509217,0.02014548,0.7152812,0.000132313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.128999,0.02640099,0.01016404,0.002557149,0.000257882,0.0000980784,0.8192095,0.00376741,0.008546022],"genre_scores_gemma":[0.06324896,0.006182217,0.01535715,0.0005257892,0.000113267,0.0001647676,0.9124657,0.0002659249,0.00167638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006659043,"threshold_uncertainty_score":0.01388961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502606245250607,"score_gpt":0.2524211100696641,"score_spread":0.237395047617158,"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."}}