{"id":"W4407723472","doi":"10.1094/pdis-10-24-2153-re","title":"Early-Season Predictions of Aerial Spores to Enhance Infection Model Efficacy for Cercospora Leaf Spot Management in Sugarbeet","year":2025,"lang":"en","type":"article","venue":"Plant Disease","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Cercospora; Fungicide; Leaf spot; Biology; Leaf wetness; Growing season; Conidium; Vapour Pressure Deficit; Horticulture; Relative humidity; Spore; Agronomy; Botany; Transpiration; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006803138,0.0004653494,0.000392971,0.0002639065,0.0001909748,0.0004407829,0.0004423211,0.0002766098,0.0008082126],"category_scores_gemma":[0.0009286737,0.0002077551,0.0002977168,0.00009694627,0.0001123801,0.0002139887,0.0001851228,0.0002784039,0.00009005838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110961,"about_ca_system_score_gemma":0.0007673249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07994099,"about_ca_topic_score_gemma":0.07605487,"domain_scores_codex":[0.9999092,0.00002772572,0.000005575677,0.0000245207,0.00001069705,0.00002219448],"domain_scores_gemma":[0.999419,0.0003437011,0.00007629471,0.00001863861,0.00009088935,0.00005156946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00037546,0.0002307253,0.06176106,0.00002960059,0.00008015311,0.00003583763,0.00004191778,0.9244547,0.004093297,0.0001500851,0.000311556,0.008435497],"study_design_scores_gemma":[0.00001339059,0.0000919666,0.008760672,0.000001953619,0.00001400811,0.000004060144,0.00001095912,0.9903815,0.0006197468,0.00003598387,0.00006141968,0.000004279469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970998,0.0000397459,0.002146786,0.00002740254,0.00000308283,0.00001375612,0.0001505821,0.00008017943,0.0004387123],"genre_scores_gemma":[0.9984341,0.00001631712,0.00111594,0.000007363819,0.000001101925,0.000008979883,0.0001457447,0.000004937125,0.0002655081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07994099,"threshold_uncertainty_score":0.1589513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00857052769581118,"score_gpt":0.2649185347874005,"score_spread":0.2563480070915893,"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."}}