{"id":"W4392349828","doi":"10.18280/ts.410116","title":"A Comparative Study of Convolutional Neural Network Architectures for Enhanced Tomato Leaf Disease Classification Using Refined Statistical Features","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Pattern recognition (psychology); Artificial intelligence; Artificial neural network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001279825,0.0001562882,0.0002148417,0.000013152,0.0001830557,0.00006410966,0.0001164562,0.00003570463,0.0001613755],"category_scores_gemma":[0.00001135417,0.00005941648,0.00008757722,0.00021516,0.00005885705,0.00003848757,0.00002355621,0.00008731349,0.000001601247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002513973,"about_ca_system_score_gemma":0.00001685139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002900553,"about_ca_topic_score_gemma":0.0002336453,"domain_scores_codex":[0.9988316,0.0001001054,0.0002734721,0.0003086417,0.0002631104,0.0002230233],"domain_scores_gemma":[0.9993266,0.0004023715,0.00006733269,0.00003210584,0.00007576752,0.00009584265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002620969,0.002357094,0.006196002,0.0001720677,0.0005094675,0.00002152119,0.003163634,0.03147396,0.8955891,0.0132897,0.0247621,0.01984443],"study_design_scores_gemma":[0.0006058335,0.001398281,0.9432572,0.00008412021,0.0001881895,0.000004177233,0.001572269,0.04824585,0.001524505,0.001406301,0.001404004,0.000309297],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974011,0.0002322445,0.0006978537,0.0004268347,0.0001415037,0.0007581959,0.0002372611,0.000062441,0.00004259656],"genre_scores_gemma":[0.9984028,6.439316e-7,0.0002868117,0.00008090901,0.0007078137,0.00009951615,0.0003823423,0.000001229018,0.00003789815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9370612,"threshold_uncertainty_score":0.2422934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05613189095295255,"score_gpt":0.2976418071438141,"score_spread":0.2415099161908615,"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."}}