{"id":"W2768129370","doi":"10.1016/j.ijfoodmicro.2017.11.016","title":"MALDI-TOF MS as a tool to identify foodborne yeasts and yeast-like fungi","year":2017,"lang":"en","type":"article","venue":"International Journal of Food Microbiology","topic":"Yeasts and Rust Fungi Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bruker (Canada)","funders":"","keywords":"Debaryomyces hansenii; Food spoilage; Yeast; Rhodotorula; Biology; Food industry; Food science; Matrix-assisted laser desorption/ionization; Mass spectrometry; Microbiology; Chemistry; Chromatography; Genetics; Bacteria","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001757483,0.0001366758,0.0001931993,0.00008940317,0.0001128978,0.00008299571,0.0005634109,0.0001133665,0.00005984183],"category_scores_gemma":[0.0002219127,0.0001127713,0.0001208416,0.0000139949,0.0001117013,0.00001143357,0.0004319744,0.0001079979,0.00003597995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001490373,"about_ca_system_score_gemma":0.00006811483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000132207,"about_ca_topic_score_gemma":0.00005277493,"domain_scores_codex":[0.9992118,0.00002719177,0.0002924808,0.000205608,0.00008411575,0.0001787834],"domain_scores_gemma":[0.9990179,0.00001152889,0.0003091202,0.0002050343,0.0003783158,0.00007810559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003288379,0.00005290878,0.002482947,0.000003854057,0.0005892939,0.00003650811,0.00006441649,0.000004817543,0.9816359,0.0002321783,0.008283447,0.00628495],"study_design_scores_gemma":[0.003039198,0.003469221,0.080268,0.0001749771,0.00009776453,0.005041318,0.0001423723,0.000001712431,0.3407646,0.0005215937,0.5659676,0.00051173],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99409,0.001726605,0.0002226979,0.001345819,0.001726613,0.00008022403,0.0001058545,0.000002766501,0.0006994],"genre_scores_gemma":[0.9967723,0.0003983701,0.0005010034,0.0006944223,0.000793261,0.000002932645,0.00001959815,0.00001332672,0.0008048075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6408713,"threshold_uncertainty_score":0.4598681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01140813491184754,"score_gpt":0.2922882814671021,"score_spread":0.2808801465552545,"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."}}