{"id":"W4406619068","doi":"10.1111/ele.70062","title":"Impacts of Weather Anomalies and Climate on Plant Disease","year":2025,"lang":"en","type":"review","venue":"Ecology Letters","topic":"Plant Pathogens and Resistance","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Environmental Health Sciences; Fogarty International Center; National Institute of Allergy and Infectious Diseases; Stanford Woods Institute for the Environment; U.S. Department of Agriculture; Stanford University Center for Innovation in Global Health; National Institutes of Health; National Science Foundation; National Institute of General Medical Sciences; Stanford King Center on Global Development","keywords":"Climate change; Maladaptation; Agriculture; Outbreak; Ecology; Precipitation; Disease; Ecosystem; Vulnerability (computing); Global warming; Climatology; Environmental science; Geography; Biology; Meteorology; Medicine","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":[0.00008839266,0.0001836702,0.0006126338,0.00002407178,0.00007715121,0.00001143867,0.0001425426,0.0001213877,0.00005228593],"category_scores_gemma":[0.0000254552,0.00005792507,0.0001588893,0.00009110026,0.00008104195,0.00001442735,0.00005789081,0.0001021381,0.000010718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001608497,"about_ca_system_score_gemma":0.00001260379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005975923,"about_ca_topic_score_gemma":0.0002417702,"domain_scores_codex":[0.999157,0.0001058522,0.0002043196,0.000250747,0.00005511751,0.0002269702],"domain_scores_gemma":[0.99927,0.0004536023,0.0001532064,0.00004937206,0.000005476238,0.00006830633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002345084,0.0003826689,0.02432398,0.02600839,0.0005278321,0.001069186,0.00002233976,0.000001000243,0.004054046,0.001020342,0.0203986,0.9219571],"study_design_scores_gemma":[0.00006206758,0.000106169,0.09489671,0.004600557,0.0003012395,0.00001363446,0.000004793269,3.666973e-7,0.000002435184,0.000008008592,0.8997566,0.0002474065],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.07204919,0.9240909,1.844654e-8,0.0006898904,0.000158652,0.000263224,0.002554048,0.00001705641,0.0001770245],"genre_scores_gemma":[0.001072801,0.9978882,0.000005392149,0.0006354747,0.00006726837,0.00001609832,0.0002338568,7.813974e-7,0.00008013303],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9217097,"threshold_uncertainty_score":0.2362116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01473965940652751,"score_gpt":0.2323101768803796,"score_spread":0.2175705174738521,"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."}}