{"id":"W1989564302","doi":"10.1186/1756-0500-7-651","title":"Estimating overannotation across prokaryotic genomes using BLAST+, UBLAST, LAST and BLAT","year":2014,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Wilfrid Laurier University","keywords":"Genome; Computer science; Bioinformatics; Computational biology; Biology; 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":[0.0008433148,0.0001315806,0.0001371139,0.00004740577,0.0003963451,0.0001060088,0.0001294832,0.0000794625,0.000003069508],"category_scores_gemma":[0.0007558107,0.0001095334,0.00003974876,0.0001044575,0.0002268887,0.000002325849,0.000330728,0.0001190204,0.000006700717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000137337,"about_ca_system_score_gemma":0.00006780196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005005422,"about_ca_topic_score_gemma":0.0001657445,"domain_scores_codex":[0.9986466,0.0001577147,0.000168038,0.0003740603,0.0002118351,0.0004417978],"domain_scores_gemma":[0.9992385,0.0001968377,0.00004787699,0.0002386399,0.0001907475,0.00008739728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006128242,0.00003398574,0.1991048,0.0001247399,0.00004598878,7.88948e-7,0.0004401886,0.005517112,0.7797764,0.00006759819,0.000063963,0.01476315],"study_design_scores_gemma":[0.003089045,0.001941454,0.4322815,0.0002232173,0.00004918665,0.00007052663,0.0009946633,0.2851208,0.260031,0.004186266,0.01079829,0.001214084],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922542,0.001146284,0.006093929,0.0000550373,0.00009490666,0.0002177249,0.00001163372,0.000004451048,0.0001218632],"genre_scores_gemma":[0.9810547,0.0001054281,0.01815461,0.00002507283,0.0005291725,0.00001837262,0.00001217198,0.00002392508,0.00007657985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5197454,"threshold_uncertainty_score":0.4466641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09816192603766524,"score_gpt":0.3910425659264569,"score_spread":0.2928806398887916,"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."}}