{"id":"W2916938152","doi":"10.3389/fmicb.2019.00315","title":"Fungal Community Ecology Using MALDI-TOF MS Demands Curated Mass Spectral Databases","year":2019,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Fundação para a Ciência e a Tecnologia; Universidad de La Frontera; Conselho Nacional de Desenvolvimento Científico e Tecnológico; European Regional Development Fund; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Ecology; Database; Microbial ecology; Mass spectrometry; Biology; Computational biology; Computer science; Chemistry; Bacteria; Chromatography; Genetics","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":[0.0005123048,0.0001859988,0.000306732,0.0001090062,0.0001129556,0.00002041737,0.000341295,0.0002521854,0.0001533063],"category_scores_gemma":[0.0001650038,0.0001978852,0.00007130607,0.0001347195,0.0001815189,0.00001041244,0.0001733146,0.0003348,0.00002965212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006765917,"about_ca_system_score_gemma":0.00009540519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001807156,"about_ca_topic_score_gemma":0.0004335067,"domain_scores_codex":[0.9981971,0.000613856,0.0003640607,0.000401054,0.00002485894,0.0003991016],"domain_scores_gemma":[0.9991412,0.00003272257,0.0001332784,0.0005752185,0.00006549881,0.00005203755],"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":[0.0000766489,0.00005438231,0.3335896,0.00001613524,0.00002612094,0.000001996747,0.00002957328,0.00004275947,0.6638567,0.00001292128,0.002240981,0.00005226068],"study_design_scores_gemma":[0.003746456,0.0007418709,0.2210087,0.00007237659,0.00007056714,0.0002902041,0.001486154,0.002088413,0.7326475,0.0003055829,0.03632019,0.001221992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951372,0.0001995912,0.001907183,0.00004953473,0.002013481,0.0002542292,0.0001224859,0.000020966,0.0002953627],"genre_scores_gemma":[0.9863379,0.00003712412,0.01129748,0.0002391166,0.0001109681,0.000005849197,0.001461475,0.00002123228,0.0004888665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1125809,"threshold_uncertainty_score":0.8069524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154462074774867,"score_gpt":0.2623979901790754,"score_spread":0.2408533694313268,"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."}}