{"id":"W2891034603","doi":"10.1007/s00216-018-1315-0","title":"Characterization and mapping of secondary metabolites of Streptomyces sp. from caatinga by desorption electrospray ionization mass spectrometry (DESI–MS)","year":2018,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Mass spectrometry; Chemistry; Desorption electrospray ionization; Chromatography; Electrospray ionization; Electrospray mass spectrometry; Characterization (materials science); Analytical Chemistry (journal); Environmental chemistry; Electrospray; Ionization; Chemical ionization; Nanotechnology; Materials science; Organic chemistry; Ion","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":[0.0001112135,0.0004521021,0.000246055,0.000733797,0.0002842945,0.0004592663,0.0001306529,0.0002279109,0.0006193137],"category_scores_gemma":[0.0002197924,0.0001130865,0.0002755062,0.00057511,0.0002034799,0.0002801666,0.00021841,0.0003337229,0.000466988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368722,"about_ca_system_score_gemma":0.0003164287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001475784,"about_ca_topic_score_gemma":0.001167724,"domain_scores_codex":[0.9998885,0.00001106629,0.00001097839,0.00003423729,0.00003669442,0.00001850959],"domain_scores_gemma":[0.9997994,0.00004054119,0.00004616757,0.00001732318,0.0000539092,0.00004275373],"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":[0.0000584847,0.000009927357,0.0005463398,0.0000155777,0.000002884533,0.00004363703,0.00001432239,0.00001834225,0.9975975,0.00001254744,0.00001108681,0.001669344],"study_design_scores_gemma":[0.00001178617,0.0002817394,0.06241294,0.00001028496,0.00004144448,0.0007072227,0.0001122193,0.0005246907,0.932117,0.00006840199,0.003697935,0.00001429194],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896247,0.001322184,0.003831541,0.00008122074,0.00002039282,0.00004776219,0.002526757,0.00007643376,0.002469],"genre_scores_gemma":[0.9809086,0.001094993,0.009881348,0.00007556682,0.00002635994,0.00004814721,0.005528642,0.00005654337,0.00237988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001475784,"threshold_uncertainty_score":0.002934456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007814774378911904,"score_gpt":0.2220464887564026,"score_spread":0.2142317143774907,"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."}}