{"id":"W4409592216","doi":"10.1101/2025.04.15.648955","title":"Genomic and Bioinformatic Insights into <i>Enterococcus faecalis</i> from Retail Meats in Nigeria","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency; University of Guelph; University of Saskatchewan","funders":"","keywords":"Enterococcus faecalis; Business; Biotechnology; Biology; Food science; Gene; Genetics; Escherichia coli","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001879375,0.0002942594,0.0002588093,0.001293125,0.0004090269,0.000777096,0.0001135332,0.0002944303,0.0006424868],"category_scores_gemma":[0.000432978,0.000164824,0.0002337607,0.001566863,0.0002287161,0.0002005153,0.0003375574,0.0001997246,0.0002497592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002314219,"about_ca_system_score_gemma":0.0003044194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004854431,"about_ca_topic_score_gemma":0.008947087,"domain_scores_codex":[0.9998292,0.00001729266,0.0000234226,0.00006396354,0.00002556143,0.00004051797],"domain_scores_gemma":[0.9997384,0.00004374661,0.0001055038,0.0000132624,0.00006699927,0.0000321238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004775761,0.0001075222,0.7817853,0.0005936177,0.00007767746,0.002123161,0.002962345,0.0005665923,0.1755318,0.0001706314,0.000564749,0.03503899],"study_design_scores_gemma":[0.000005010529,0.00009535742,0.9800683,0.0001375029,0.00006090142,0.002192323,0.005229583,0.0005210355,0.006687376,0.00009774564,0.004894811,0.0000101034],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969947,0.0004686934,0.0003560741,0.00006179845,0.000006786664,0.0000151743,0.001302296,0.000007356492,0.0007871772],"genre_scores_gemma":[0.9937161,0.000648517,0.001590897,0.00007190663,0.000007229537,0.00001426261,0.003378956,0.000009392727,0.0005627921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004854431,"threshold_uncertainty_score":0.009652376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185056914525969,"score_gpt":0.2226397177856076,"score_spread":0.2107891486403479,"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."}}