{"id":"W2605148313","doi":"10.1016/j.vetmic.2017.03.036","title":"Species level identification of coagulase negative Staphylococcus spp. from buffalo using matrix-assisted laser desorption ionization–time of flight mass spectrometry and cydB real-time quantitative PCR","year":2017,"lang":"en","type":"article","venue":"Veterinary Microbiology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Division of Graduate Education; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; University of Guelph","keywords":"Biology; Staphylococcus epidermidis; Staphylococcus; Microbiology; Mass spectrometry; Matrix-assisted laser desorption/ionization; Species identification; Veterinary medicine; Bacteria; Staphylococcus aureus; Chromatography; Chemistry; Genetics; Medicine","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":[0.0002886439,0.000268137,0.0003197671,0.0007744672,0.0003105765,0.0003962228,0.0001683611,0.0002589547,0.001070075],"category_scores_gemma":[0.0004369787,0.0001653651,0.0001757124,0.000466687,0.0002777398,0.0002573426,0.0002210565,0.0002757017,0.0003058407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001828459,"about_ca_system_score_gemma":0.0003375558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001722996,"about_ca_topic_score_gemma":0.003123956,"domain_scores_codex":[0.9997012,0.00002371665,0.000033488,0.00008633483,0.0001167782,0.00003849701],"domain_scores_gemma":[0.9997142,0.00006224817,0.00006541383,0.00001106936,0.0001217601,0.00002529621],"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":[0.0001092902,0.00002911188,0.008105235,0.00004827511,0.000007520759,0.00006219722,0.0001028447,0.00003207032,0.9888442,0.00003587266,0.00005603607,0.002567216],"study_design_scores_gemma":[0.0000176467,0.0009163208,0.3449952,0.00006236866,0.0001438192,0.001366058,0.0007495779,0.002712611,0.6432276,0.000213514,0.005547259,0.00004804887],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990399,0.0009752841,0.004714711,0.00009137565,0.00003180944,0.00006771379,0.002364759,0.00005427222,0.001301096],"genre_scores_gemma":[0.9696685,0.001258188,0.02127681,0.0001321079,0.00004185792,0.0001915943,0.003722782,0.00004428175,0.003663862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001722996,"threshold_uncertainty_score":0.003579795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05447109163755256,"score_gpt":0.3046152066983933,"score_spread":0.2501441150608407,"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."}}