{"id":"W4398245406","doi":"10.1002/ppj2.20103","title":"Estimating Fusarium head blight severity in winter wheat using deep learning and a spectral index","year":2024,"lang":"en","type":"article","venue":"The Plant Phenome Journal","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Fusarium; Index (typography); Winter wheat; Head (geology); Agronomy; Blight; Environmental science; Mathematics; Horticulture; Biology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003703001,0.0001766963,0.0002479631,0.0002193249,0.0002566863,0.000373606,0.0001725755,0.0000739869,0.000909759],"category_scores_gemma":[0.0000549794,0.0001231606,0.0000757185,0.0003653109,0.00006136671,0.0002011065,0.00007703086,0.001283424,0.000008071627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002014495,"about_ca_system_score_gemma":0.00005016769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005562335,"about_ca_topic_score_gemma":0.00003322594,"domain_scores_codex":[0.9988707,0.00003787946,0.0003092489,0.0001994429,0.0002093686,0.0003733062],"domain_scores_gemma":[0.999544,0.0001683514,0.00008573775,0.00009038092,0.00001609671,0.0000954061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005566551,0.0002998381,0.3015316,0.0009907428,0.001374921,0.002021559,0.01652477,0.01677926,0.6513819,0.0003234545,0.000423161,0.007792095],"study_design_scores_gemma":[0.001096539,0.00007997297,0.005238601,0.0007400615,0.0005153449,0.01116926,0.003867283,0.9456044,0.02575659,0.003611127,0.001568837,0.000751993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875684,0.004542091,0.003517837,0.0003083652,0.0001576222,0.0000250928,0.000008792647,0.00004983001,0.003821951],"genre_scores_gemma":[0.9975463,0.0001003844,0.001012982,0.0000362445,0.0008100197,9.919867e-7,0.000005104858,0.00002031257,0.0004676652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9288251,"threshold_uncertainty_score":0.9961224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293843411685579,"score_gpt":0.2867101800118707,"score_spread":0.2637717458950148,"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."}}