{"id":"W2951584314","doi":"10.1093/nar/gkx702","title":"Neptune: a bioinformatics tool for rapid discovery of genomic variation in bacterial populations","year":2017,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Maple Leaf Foods; University of British Columbia; Ste. Anne's Hospital; Université de Montréal; Canadian Food Inspection Agency; Provincial Laboratory of Public Health; McMaster University; Alberta Innovates; University of Alberta; Health Canada; University of Manitoba; Public Health Agency of Canada","funders":"Health Canada; Public Health Agency","keywords":"Biology; Neptune; Genomics; Computational biology; Genome; Comparative genomics; Genetics; Bacterial genome size; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002978654,0.002374605,0.00331664,0.003265721,0.00140934,0.002215779,0.003087736,0.00137654,0.01609732],"category_scores_gemma":[0.008431989,0.001782684,0.00251932,0.002919252,0.0007318921,0.002196954,0.002852727,0.002986009,0.007924629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009095836,"about_ca_system_score_gemma":0.001686757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002351616,"about_ca_topic_score_gemma":0.004421639,"domain_scores_codex":[0.9988964,0.0002883298,0.0001035025,0.000355846,0.0002838286,0.00007213308],"domain_scores_gemma":[0.997768,0.001496247,0.0002383055,0.0001830392,0.0001630382,0.0001512341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00544808,0.0006926466,0.02209145,0.008873897,0.002910385,0.003338567,0.003067773,0.03244367,0.1199632,0.02315086,0.4197947,0.3582247],"study_design_scores_gemma":[0.002179697,0.0006632979,0.02366327,0.0008436881,0.0008114687,0.003570493,0.0005788064,0.4908434,0.05873102,0.06369647,0.3537712,0.0006471224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02222338,0.001604851,0.5823973,0.0006412464,0.00039403,0.0005160371,0.07045089,0.3168237,0.004948557],"genre_scores_gemma":[0.06216596,0.001224427,0.829728,0.0006190226,0.0001190495,0.002523312,0.0765813,0.02371104,0.003328013],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01609732,"threshold_uncertainty_score":0.05385095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05803935283509574,"score_gpt":0.34040044302896,"score_spread":0.2823610901938642,"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."}}