{"id":"W4311163351","doi":"10.18280/ts.390537","title":"Hybrid Deep Model for Automated Detection of Tomato Leaf Diseases","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Artificial intelligence; Deep learning; Feature (linguistics); Computer science; Pattern recognition (psychology); Feature extraction; Artificial neural network; Process (computing); Machine learning","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":[0.0002889613,0.0008776364,0.0005233737,0.0006489349,0.0002352065,0.0005471673,0.0009479334,0.0007280092,0.001598792],"category_scores_gemma":[0.0003736273,0.0003085901,0.0006969569,0.0003187447,0.0001527916,0.0006552238,0.000508951,0.0007595338,0.0005777233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008295117,"about_ca_system_score_gemma":0.0009042037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01383549,"about_ca_topic_score_gemma":0.01679735,"domain_scores_codex":[0.9998467,0.00001437004,0.000009543809,0.00005382498,0.00003246076,0.00004316854],"domain_scores_gemma":[0.9998726,0.00002690368,0.00001545128,0.00001262884,0.00005756763,0.00001482887],"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":[0.000696544,0.000731107,0.01155007,0.0001991737,0.0002756338,0.0004199852,0.00009172782,0.4715751,0.04654887,0.001902383,0.0127743,0.4532351],"study_design_scores_gemma":[0.00000560436,0.00003246964,0.0007691444,0.000005102308,0.00001138579,0.0000161769,0.000005138933,0.9962193,0.002306242,0.0002751389,0.0003492234,0.000005132781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.398794,0.003782249,0.5721299,0.0009982227,0.0004130475,0.0002320483,0.00241015,0.01137618,0.009864209],"genre_scores_gemma":[0.9221398,0.0005543407,0.06447659,0.0003667673,0.00005824982,0.0001384785,0.00270349,0.00007144217,0.009490857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01383549,"threshold_uncertainty_score":0.02750993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438620035748171,"score_gpt":0.2048056572628177,"score_spread":0.190419456905336,"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."}}