{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005356816,0.0002888985,0.0002371493,0.00003829898,0.0001867068,0.0001042381,0.0009126402,0.0002285552,0.000004685343],"category_scores_gemma":[0.0001865757,0.0002073085,0.00005317175,0.0001149547,0.0002715414,0.00003929828,0.0005361443,0.00006483648,0.00001822906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005971537,"about_ca_system_score_gemma":0.0004231953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001400165,"about_ca_topic_score_gemma":0.000130533,"domain_scores_codex":[0.9983459,0.0001296334,0.0004588191,0.0005937387,0.00006929444,0.0004026329],"domain_scores_gemma":[0.9979113,0.00002669462,0.0002870393,0.001363929,0.0003088045,0.0001021964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005039201,0.00001831752,0.0002024075,0.00003071447,0.0000491844,0.000001666387,0.00004310134,0.0001436927,0.9976155,0.0001153196,0.0003990695,0.0008771466],"study_design_scores_gemma":[0.002070857,0.0009445346,0.00007745095,0.00002224246,0.0001145494,0.0005856042,0.0001033534,0.01760087,0.6026172,0.0000380268,0.3750558,0.0007695323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8377557,0.0008873109,0.1569218,0.0002465548,0.0008598418,0.001219071,0.002014804,0.00004094194,0.00005394975],"genre_scores_gemma":[0.9140018,0.0002450933,0.02335482,0.001352334,0.0007118231,0.0002364546,0.05928538,0.00008579502,0.000726496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3949983,"threshold_uncertainty_score":0.8453795,"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."}}