{"id":"W4206618551","doi":"10.1109/access.2022.3142817","title":"Beans Leaf Diseases Classification Using MobileNet Models","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":219,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Leaf spot; Rust (programming language); Deep learning; Computer science; Hyperparameter; Contextual image classification; Artificial intelligence; Architecture; Pattern recognition (psychology); Machine learning; Image (mathematics); Horticulture; Biology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002380963,0.001365761,0.0004874534,0.0008980369,0.0002283192,0.0005096003,0.0007391667,0.0007432926,0.001155317],"category_scores_gemma":[0.0004282566,0.0002076481,0.0007462224,0.0004181664,0.0001550688,0.0006241984,0.000326065,0.0005429139,0.0005478465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087582,"about_ca_system_score_gemma":0.0004986388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02075202,"about_ca_topic_score_gemma":0.02651886,"domain_scores_codex":[0.99989,0.00001109676,0.000005936267,0.00004385267,0.00001772376,0.00003132354],"domain_scores_gemma":[0.9998857,0.00002375283,0.00001657043,0.000009597366,0.00004978666,0.00001451413],"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":[0.0009771709,0.000638015,0.02377169,0.0002845493,0.0003208683,0.0006207596,0.000138106,0.5633249,0.02629739,0.002079087,0.0196116,0.3619358],"study_design_scores_gemma":[0.000009207471,0.00006768492,0.001811018,0.00001580504,0.00002217343,0.00003852479,0.00002423898,0.993443,0.002681759,0.0006204028,0.001257138,0.000009123505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.792327,0.005119864,0.175858,0.001516301,0.0007481014,0.0001977176,0.004821816,0.008562987,0.01084836],"genre_scores_gemma":[0.9480687,0.0007764607,0.03633747,0.0004008398,0.000120722,0.00008165398,0.007003135,0.0001019433,0.007109145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02075202,"threshold_uncertainty_score":0.04126245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1060395078041815,"score_gpt":0.2822540764757433,"score_spread":0.1762145686715618,"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."}}