{"id":"W4401073231","doi":"10.1007/978-3-031-64847-2_18","title":"Rice Leaf Disease Diagnosis Using Dense EfficientNet Model","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Agronomy; Environmental science; Biology; Horticulture","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000176368,0.0004706129,0.0005213431,0.00003266411,0.0001674688,0.0002799029,0.0001883832,0.0005656588,0.00003678025],"category_scores_gemma":[0.0000208495,0.0001693637,0.0001886822,0.0001472814,0.00006339265,0.00004727833,0.0001237335,0.0005465235,0.00001242565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006190926,"about_ca_system_score_gemma":0.00001117443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001882651,"about_ca_topic_score_gemma":0.0005266615,"domain_scores_codex":[0.9982257,0.00003265389,0.0003898894,0.0006825922,0.0002705902,0.0003985653],"domain_scores_gemma":[0.9991,0.0004105504,0.0001332286,0.000103141,0.00005175433,0.0002013067],"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":[0.00006873117,0.00005949139,0.002196471,0.0003283547,0.000118983,0.0002887445,0.0001381604,0.9746233,0.0003626322,0.006057295,0.003745152,0.01201265],"study_design_scores_gemma":[0.0001678084,0.0001185603,0.0007702006,0.002760277,0.0003448409,0.00005232168,0.00001542459,0.9181367,0.000005446655,0.007790319,0.06855237,0.001285755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.315802,0.6152046,0.005610283,0.00342634,0.009440465,0.005386746,0.001122318,0.0008386514,0.0431686],"genre_scores_gemma":[0.9840107,0.001679312,0.00001477471,0.0003236871,0.00301487,0.00004200783,0.0001891896,0.000009244355,0.01071624],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6682086,"threshold_uncertainty_score":0.6906452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02576108023951483,"score_gpt":0.2180736654009277,"score_spread":0.1923125851614128,"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."}}