{"id":"W3016361142","doi":"10.3390/rs12081292","title":"Potato Late Blight Detection at the Leaf and Canopy Levels Based in the Red and Red-Edge Spectral Regions","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; A&L Canada Laboratories (Canada); University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Blight; Red edge; Canopy; Phytophthora infestans; Horticulture; Botany; Biology; Remote sensing; Geography","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":[0.0002764273,0.0001713755,0.0001425046,0.00002140678,0.0003761905,0.00008549273,0.00009721721,0.00008885073,0.00001168617],"category_scores_gemma":[0.0001054611,0.00009929514,0.00004020327,0.0004338212,0.0002299616,0.00008448144,0.0001029205,0.0003041729,0.00001981657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001606279,"about_ca_system_score_gemma":0.000009061446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000419352,"about_ca_topic_score_gemma":0.003452137,"domain_scores_codex":[0.9986604,0.0002408518,0.0001754917,0.0003903076,0.0002508686,0.0002820526],"domain_scores_gemma":[0.9994441,0.0001288701,0.00007997779,0.0002498164,0.000007301792,0.0000899283],"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":[0.00006162654,0.000007137943,0.000426336,0.00001322498,0.00001066531,0.0001510089,0.005829152,0.002261505,0.9422551,0.000003598094,0.002863569,0.04611701],"study_design_scores_gemma":[0.001237341,0.0001598843,0.1740714,0.0001459571,0.0000890329,0.001103922,0.001068612,0.6720741,0.1185676,0.0008430409,0.02993281,0.0007062501],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9640548,0.00004749688,0.000703882,0.03142641,0.00007016957,0.0002873629,0.000001565638,0.00004366516,0.00336466],"genre_scores_gemma":[0.9956173,0.0000231648,0.002148999,0.001881094,0.00008589286,1.030514e-8,0.000002042892,0.00001571884,0.0002257633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8236876,"threshold_uncertainty_score":0.4049138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821565851208425,"score_gpt":0.209906753766555,"score_spread":0.1916910952544707,"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."}}