{"id":"W3034307258","doi":"10.3390/metabo10060238","title":"Chemotaxonomic Profiling of Canadian Alternaria Populations Using High-Resolution Mass Spectrometry","year":2020,"lang":"en","type":"article","venue":"Metabolites","topic":"Fungal Plant Pathogen Control","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Western University","funders":"Agriculture and Agri-Food Canada; Government of Canada","keywords":"Profiling (computer programming); Alternaria; Mass spectrometry; Computational biology; High resolution; Biology; Chromatography; Chemistry; Computer science; Botany; Geography; Remote sensing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002352746,0.0004024958,0.0002477844,0.001710748,0.0009141889,0.0006026725,0.0003041719,0.0001956676,0.0007326971],"category_scores_gemma":[0.0003645404,0.0001264037,0.0002622373,0.001743687,0.0002836177,0.0001507979,0.0003196592,0.0002626705,0.000151728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00268687,"about_ca_system_score_gemma":0.003309119,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.63301,"about_ca_topic_score_gemma":0.7834171,"domain_scores_codex":[0.9996543,0.00001344424,0.00001518107,0.00007029241,0.0001837303,0.00006302977],"domain_scores_gemma":[0.9996601,0.00001287923,0.00004413288,0.000007883733,0.0002312532,0.00004373005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004667169,0.0001570386,0.08419046,0.0001103675,0.00005887934,0.0001942282,0.0007018006,0.0005850603,0.8840171,0.0001956036,0.0004849303,0.02883767],"study_design_scores_gemma":[0.00003239689,0.0004614285,0.8839289,0.00001977925,0.0001055548,0.0004015467,0.001121196,0.001991992,0.1058765,0.00007912453,0.005930556,0.00005106214],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947937,0.0002784641,0.0007312315,0.00006823866,0.000005253582,0.00006818636,0.002230543,0.00003474159,0.001789578],"genre_scores_gemma":[0.9881093,0.0006430322,0.005493316,0.00006567334,0.000003897072,0.00003279294,0.003191336,0.00001367133,0.002447055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.36699,"threshold_uncertainty_score":0.7383026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0609768191525773,"score_gpt":0.2164811646492105,"score_spread":0.1555043454966332,"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."}}