{"id":"W3043135777","doi":"10.1038/s41396-020-0720-5","title":"Predicting disease occurrence with high accuracy based on soil macroecological patterns of Fusarium wilt","year":2020,"lang":"en","type":"article","venue":"The ISME Journal","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":297,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; National Postdoctoral Program for Innovative Talents; Special Fund for Agro-scientific Research in the Public Interest; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; Government of Jiangsu Province; Chinese Academy of Sciences; Ministry of Education of the People's Republic of China; Institute of Genetics; National Natural Science Foundation of China","keywords":"Biology; Fusarium oxysporum; Fusarium wilt; Fusarium; Microbiome; Soil microbiology; Soil water; Wilt disease; Agronomy; Botany; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001263923,0.0007501491,0.0005733097,0.001671293,0.0002425902,0.0009545757,0.0003191783,0.0005345,0.0003752164],"category_scores_gemma":[0.002194617,0.0002148761,0.0006501235,0.0006097479,0.0001660413,0.0006100487,0.0004035304,0.0003878766,0.0003197833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00036503,"about_ca_system_score_gemma":0.0003711989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008863622,"about_ca_topic_score_gemma":0.010507,"domain_scores_codex":[0.9996372,0.00009329334,0.00003062904,0.0001444905,0.00004090204,0.00005342926],"domain_scores_gemma":[0.9988779,0.0006032998,0.0002168135,0.00007882385,0.0001535796,0.00006944674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003277311,0.0002306092,0.8624521,0.00006734806,0.0002974331,0.0001108905,0.00008577952,0.05901613,0.0127755,0.0000639867,0.0006286757,0.0639438],"study_design_scores_gemma":[0.00002459567,0.0001823585,0.4260114,0.00002845799,0.0001229869,0.0001327837,0.0002513954,0.5683151,0.003688634,0.0005115355,0.0006981803,0.00003253211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980683,0.0004067179,0.01688367,0.00009086829,0.00001336658,0.00003178381,0.001113207,0.0002581353,0.000519403],"genre_scores_gemma":[0.9895902,0.0001164833,0.00869623,0.0000304179,0.00001082647,0.00001433127,0.001385013,0.000009300634,0.0001470567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008863622,"threshold_uncertainty_score":0.01762408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406841540972623,"score_gpt":0.2275301098730996,"score_spread":0.2134616944633734,"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."}}