{"id":"W2089083615","doi":"10.1038/nprot.2010.78","title":"Gene function analysis in complex data sets using ErmineJ","year":2010,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":145,"is_retracted":false,"has_abstract":false,"ca_institutions":"Michael Smith Health Research BC; University of British Columbia","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research","keywords":"Computational biology; Function (biology); Biology; Computer science; Bioinformatics; Genetics","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":[0.0003245139,0.0001227953,0.0001562296,0.00008628575,0.00005058898,0.00004140145,0.0003811484,0.0004754825,0.0000437249],"category_scores_gemma":[0.00003120946,0.000110975,0.0000575895,0.0002893412,0.00003159541,0.000007599676,0.0002532194,0.0004553884,0.000003619774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007201375,"about_ca_system_score_gemma":0.00005402624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001519225,"about_ca_topic_score_gemma":0.0005137104,"domain_scores_codex":[0.9991615,0.00002222117,0.0002276078,0.0002910305,0.0001050374,0.000192562],"domain_scores_gemma":[0.9989393,0.00000496714,0.0001024189,0.0008467056,0.00005396181,0.00005258679],"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":[0.0002273769,0.0001157713,0.02361574,0.00004863575,0.0003246055,0.000004066397,0.00002321982,0.0007941644,0.948096,0.0001072806,0.0057158,0.02092736],"study_design_scores_gemma":[0.002939219,0.0002934745,0.08743381,0.00003202298,0.0003715837,0.00004861333,0.00002996658,0.2457668,0.03865109,0.0007942016,0.6226345,0.001004708],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235219,0.0002147774,0.02042379,0.000241173,0.0003928233,0.05213062,0.0004234422,0.00004049879,0.002610942],"genre_scores_gemma":[0.9725604,0.000002266695,0.02160112,0.0005609175,0.0003774212,0.002455449,0.002365961,0.0000166663,0.0000598137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9094449,"threshold_uncertainty_score":0.452543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465628421779254,"score_gpt":0.3506111704642645,"score_spread":0.315954886246472,"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."}}