{"id":"W2944645675","doi":"10.3389/fmicb.2019.01020","title":"Whole Genome Sequencing and Metabolomic Study of Cave Streptomyces Isolates ICC1 and ICC4","year":2019,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Thompson Rivers University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Secondary metabolite; Biology; Genome; Streptomyces; Metabolome; Metabolite; Metabolomics; Whole genome sequencing; Genomics; Secondary metabolism; Gene; Polyketide; Computational biology; Bacteria; Genetics; Bioinformatics; Biochemistry; Biosynthesis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001403913,0.0001485682,0.0003311987,0.00005837764,0.00003216889,0.000006932368,0.000109944,0.0001172745,0.000003339918],"category_scores_gemma":[0.00000959102,0.000137624,0.00002646707,0.00004709322,0.0001576573,0.00000111416,0.0001999001,0.00006865438,0.00000100084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001292308,"about_ca_system_score_gemma":0.00001888323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000742216,"about_ca_topic_score_gemma":0.00007441718,"domain_scores_codex":[0.9991001,0.00007381773,0.0002243866,0.0003827785,0.00001508771,0.0002038486],"domain_scores_gemma":[0.9996504,0.00001052267,0.00008944352,0.0001967578,0.00002603507,0.0000268845],"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":[0.00003854854,0.0000264194,0.3132925,0.00001271674,0.0001033599,5.788639e-7,0.000440897,0.00003290918,0.6857637,0.000002511241,0.00005494378,0.0002309049],"study_design_scores_gemma":[0.006868849,0.004419783,0.7290424,0.00003458455,0.0001993942,0.0001063106,0.02929713,0.0001480044,0.206369,0.0003697928,0.02200081,0.001143962],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861059,0.01318179,0.00002732002,0.0000194037,0.0002395954,0.0003082301,0.00005340981,0.000001558286,0.00006277535],"genre_scores_gemma":[0.9976221,0.0007509943,0.001384973,0.00004428629,0.00002800611,0.000008457451,0.00002813636,0.00001223214,0.0001208299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4793947,"threshold_uncertainty_score":0.5612143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005040180584096272,"score_gpt":0.1986845707825794,"score_spread":0.1936443901984831,"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."}}