{"id":"W1789948341","doi":"10.1186/s12866-015-0526-1","title":"The Listeria monocytogenes Core-Genome Sequence Typer (LmCGST): a bioinformatic pipeline for molecular characterization with next-generation sequence data","year":2015,"lang":"en","type":"article","venue":"BMC Microbiology","topic":"Listeria monocytogenes in Food Safety","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Biology; Multilocus sequence typing; Genome; Genetics; Computational biology; Whole genome sequencing; Phylogenetic tree; In silico; Reference genome; Locus (genetics); Sequence analysis; Gene; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003667383,0.002291771,0.001155775,0.00295658,0.0009864405,0.00165717,0.001981003,0.0009303777,0.006000335],"category_scores_gemma":[0.004318059,0.001471173,0.002001278,0.00164152,0.0005067772,0.001203822,0.001763051,0.002232526,0.005919821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00105928,"about_ca_system_score_gemma":0.002607659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003590766,"about_ca_topic_score_gemma":0.003399713,"domain_scores_codex":[0.9984792,0.0002146453,0.0001286572,0.000573337,0.0004568287,0.0001473394],"domain_scores_gemma":[0.9984724,0.0004257238,0.0002855869,0.0002488568,0.0003989431,0.000168465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003429298,0.0005259083,0.03410104,0.002599675,0.0009661309,0.001130273,0.001510262,0.0195291,0.3605268,0.005641132,0.1678985,0.4021417],"study_design_scores_gemma":[0.0007350464,0.0007732349,0.03897072,0.0004701334,0.0004995013,0.001902078,0.0003227834,0.377817,0.3825568,0.01309,0.1821872,0.0006753455],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02912943,0.000602596,0.7601408,0.0003883168,0.0001474247,0.0008301178,0.03692158,0.1696989,0.002140864],"genre_scores_gemma":[0.05612296,0.000355405,0.8676842,0.0003665035,0.0000445366,0.001123751,0.05995909,0.01250871,0.001834836],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006000335,"threshold_uncertainty_score":0.02007312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3816063400705172,"score_gpt":0.3633274466407189,"score_spread":0.01827889342979833,"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."}}