{"id":"W2336308079","doi":"10.1101/pdb.prot088880","title":"Use of the BioGRID Database for Analysis of Yeast Protein and Genetic Interactions","year":2016,"lang":"en","type":"article","venue":"Cold Spring Harbor Protocols","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute; Université de Montréal; Institute for Research in Immunology and Cancer","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; National Institutes of Health","keywords":"Schizosaccharomyces pombe; Budding yeast; Yeast; Candida albicans; Saccharomyces cerevisiae; Biology; Schizosaccharomyces; Computational biology; Database; Bioinformatics; Genetics; Computer science","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":[0.00008778613,0.00007280191,0.0001273752,0.00004828761,0.0000342626,0.00001269753,0.0001283713,0.00004183847,0.000004924667],"category_scores_gemma":[0.00006198847,0.00004521822,0.0001024265,0.000113313,0.00007596173,0.000005813358,0.0001297499,0.00002606707,2.557455e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005523048,"about_ca_system_score_gemma":0.00003367197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000138291,"about_ca_topic_score_gemma":0.00003206819,"domain_scores_codex":[0.9994694,0.00001796599,0.000228708,0.0001289493,0.00005310759,0.0001018883],"domain_scores_gemma":[0.9992876,0.00001613276,0.0001781952,0.0004109624,0.00007508539,0.00003199679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005402101,0.00002823405,0.003622884,0.00006128483,0.000194772,5.893861e-8,0.000005540097,0.00002543717,0.9945297,0.0005752665,0.00009160073,0.0008112113],"study_design_scores_gemma":[0.0005007508,0.0001266691,0.03085041,0.000205988,0.0001532392,2.440472e-7,0.000002808575,0.001264245,0.9178377,0.00001110196,0.0489287,0.0001181001],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9230172,0.00004930323,0.04338475,0.0001086056,0.00003845615,0.03291079,0.0004722584,0.000005540064,0.00001308994],"genre_scores_gemma":[0.9792331,0.000006906416,0.006320967,0.00002691945,0.00004117005,0.01425124,0.000002375961,0.00001028665,0.0001069609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07669195,"threshold_uncertainty_score":0.1843946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019394413057767,"score_gpt":0.2791532204173295,"score_spread":0.2489592762867519,"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."}}