{"id":"W6913242862","doi":"10.5683/sp2/jz77xa","title":"Comprehensive Prediction of the SARS-CoV-2 vs. Human Interactome using PIPE4, SPRINT, and PIPE-Sites","year":2020,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Interactome; Leverage (statistics); Pairwise comparison; Metadata; Protein–protein interaction; Human proteins; Interaction information; Biomedicine","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":[0.001160915,0.00203355,0.001185799,0.002058023,0.0008282252,0.0009970688,0.001686063,0.001656658,0.006726031],"category_scores_gemma":[0.002481842,0.000422019,0.001634473,0.002246395,0.0004343019,0.0007264069,0.001364365,0.001124692,0.007523003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001189102,"about_ca_system_score_gemma":0.001681905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02403622,"about_ca_topic_score_gemma":0.04623801,"domain_scores_codex":[0.999121,0.0001731541,0.00006168016,0.0003417772,0.0001806381,0.0001216887],"domain_scores_gemma":[0.9994124,0.0002278002,0.00007468509,0.0001030734,0.00009147965,0.00009049609],"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":[0.002060768,0.0005086499,0.04393541,0.003986689,0.0007695848,0.001124634,0.0001794555,0.0269497,0.008933856,0.003781972,0.8813382,0.02643108],"study_design_scores_gemma":[0.001783906,0.0006797838,0.106055,0.0007562902,0.0006940807,0.002539629,0.0006997076,0.09538466,0.01002479,0.01093185,0.7702032,0.0002470563],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02944578,0.001441227,0.001265043,0.0003339716,0.0000577582,0.00004860881,0.9630597,0.001522246,0.002825695],"genre_scores_gemma":[0.01077562,0.0002057747,0.001381467,0.00007725704,0.000006334633,0.00005268302,0.9870687,0.00004951774,0.0003827011],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02403622,"threshold_uncertainty_score":0.04779267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07783349202724608,"score_gpt":0.3221344189024333,"score_spread":0.2443009268751872,"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."}}