{"id":"W4200285707","doi":"10.18280/ria.350605","title":"Corn Leaf Disease Detection with Pertinent Feature Selection Model Using Machine Learning Technique with Efficient Spot Tagging Model","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leaf spot; Machine learning; Artificial intelligence; Computer science; Septoria; Plant disease; Feature selection; Blight; Feature (linguistics); Biotechnology; Agronomy; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.000449807,0.0005436779,0.0005872605,0.0005228803,0.0002826093,0.0005444516,0.0005969108,0.0005622435,0.0009351033],"category_scores_gemma":[0.000629776,0.0002082245,0.000784349,0.0003550674,0.0001970221,0.0003699391,0.0002557856,0.0005115287,0.0002162688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000584378,"about_ca_system_score_gemma":0.0005586221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01069046,"about_ca_topic_score_gemma":0.006120176,"domain_scores_codex":[0.9998127,0.00003322662,0.00001320998,0.00006158221,0.00004584155,0.000033447],"domain_scores_gemma":[0.9997048,0.0001450875,0.00003095089,0.00001533816,0.00009147116,0.00001229566],"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":[0.0002505669,0.0002139238,0.006013931,0.00005523295,0.000114542,0.0001849694,0.00005312725,0.8150613,0.007528862,0.001384278,0.001348806,0.1677905],"study_design_scores_gemma":[0.000002190914,0.00001746938,0.0002875679,9.987571e-7,0.000005183834,0.000008177582,0.000001284155,0.999227,0.0002804863,0.0001126018,0.00005477531,0.00000219444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2410607,0.0009050622,0.7525102,0.0005140433,0.0001159068,0.0001236177,0.0002291602,0.001277741,0.003263573],"genre_scores_gemma":[0.960097,0.000225077,0.03600293,0.00009157796,0.00003716649,0.0001241249,0.0002956274,0.00001671003,0.003109766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01069046,"threshold_uncertainty_score":0.02125645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02483961415361087,"score_gpt":0.2208805977953666,"score_spread":0.1960409836417557,"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."}}