{"id":"W3004238495","doi":"10.1038/s41598-019-56895-w","title":"PIPE4: Fast PPI Predictor for Comprehensive Inter- and Cross-Species Interactomes","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Carleton University","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Grain Farmers of Ontario","keywords":"Computational biology; Computer science; Interactome; Biology; Protein–protein interaction; Arabidopsis; Caenorhabditis elegans; Artificial intelligence; Machine learning; Bioinformatics; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001638704,0.0001291994,0.0001459422,0.00002617552,0.0001616701,0.0003215097,0.0001127384,0.00008273796,0.00002273803],"category_scores_gemma":[0.0000732842,0.0001127135,0.00008554366,0.00006626504,0.0002854157,0.000010582,0.0002126728,0.00006348533,0.000003955156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006266505,"about_ca_system_score_gemma":0.000046436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.411783e-7,"about_ca_topic_score_gemma":0.000004325995,"domain_scores_codex":[0.9988737,0.000009100282,0.0003515572,0.0004496669,0.0001046598,0.0002112801],"domain_scores_gemma":[0.9991848,0.00001178825,0.0001763279,0.0003157529,0.0001690686,0.0001422101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000173438,0.00004862981,0.01289629,0.0002343465,0.000142948,0.00003167591,0.001813649,0.000125711,0.5562743,0.0001218509,0.4196565,0.008480691],"study_design_scores_gemma":[0.0003495089,0.0002034521,0.001960055,0.00002228925,0.00001527021,0.00009049872,0.0003362292,0.002381848,0.04770701,0.0005712881,0.9461272,0.0002353518],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979522,0.0006702477,0.01425886,0.0004967195,0.003400283,0.0004591791,0.00005197764,0.00003396273,0.001106726],"genre_scores_gemma":[0.9960304,0.00001862123,0.0008674805,0.0004586085,0.0003124865,0.00001815945,0.0002987666,0.00001317362,0.001982299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5264707,"threshold_uncertainty_score":0.4596324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161912187887638,"score_gpt":0.2654608307286541,"score_spread":0.2438417088497777,"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."}}