{"id":"W3030304545","doi":"10.1186/s12864-020-6765-z","title":"Comparative genomic analysis of 142 bacteriophages infecting Salmonella enterica subsp. enterica","year":2020,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Université Laval; McGill University; Canadian Food Inspection Agency","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs; Canadian Food Inspection Agency; University of Ottawa; Genome Canada; James Madison University","keywords":"Prophage; Genome; Biology; Salmonella enterica; Comparative genomics; Genetics; Bacterial genome size; Genomics; Salmonella; GC-content; ORFS; Genome size; Computational biology; Gene; Bacteriophage; Open reading frame; Escherichia coli; Bacteria; Peptide sequence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007816252,0.0002098516,0.00051301,0.00007879821,0.0001084786,0.00005548094,0.000301412,0.00005664361,0.003576061],"category_scores_gemma":[0.00001629701,0.0002152967,0.0003006911,0.0005993173,0.000131106,0.0001484897,0.000366523,0.0001397807,0.0004516829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001804955,"about_ca_system_score_gemma":0.00001701076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004270808,"about_ca_topic_score_gemma":0.0003833615,"domain_scores_codex":[0.99869,0.00008015145,0.0004599672,0.0004053363,0.00009517707,0.0002693695],"domain_scores_gemma":[0.9991867,0.00007197454,0.0003165931,0.0002550564,0.00001455686,0.0001551107],"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":[0.00005796226,0.00007265749,0.03272778,0.00001077981,0.0002629471,0.000002516821,0.003370258,0.00456017,0.9583037,0.000001876761,0.0002561658,0.0003732065],"study_design_scores_gemma":[0.00041585,0.0002028468,0.8969229,0.000008845236,0.0007538821,0.00000992465,0.0009484721,0.009450147,0.07033461,0.000003930722,0.02051953,0.0004290415],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942528,0.00004176068,0.002842135,0.00008341895,0.0001175637,0.0001893366,0.0001092243,0.00003708784,0.002326669],"genre_scores_gemma":[0.9958233,0.00005214512,0.00355593,0.0003016132,0.00005455142,0.000007825216,0.00005038801,0.00001959195,0.000134608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8879691,"threshold_uncertainty_score":0.9973348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422112675555648,"score_gpt":0.2610268489552487,"score_spread":0.2268057221996922,"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."}}