{"id":"W4312177497","doi":"10.18280/ria.360503","title":"Enhanced Hybrid Neural Networks (CoAtNet) for Paddy Crops Disease Detection and Classification","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Staple food; Blight; Agriculture; Leaf spot; Paddy field; Oryza sativa; Tamil; Rice plant; Agronomy; Biotechnology; 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":[0.0003965591,0.0007471335,0.0004034938,0.0006148829,0.0002267437,0.0005208394,0.000832313,0.0006829174,0.001586843],"category_scores_gemma":[0.0005044987,0.0002397404,0.0004195205,0.0003982211,0.0001496073,0.0006157162,0.0003402233,0.0005113849,0.0004891533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007250949,"about_ca_system_score_gemma":0.0005302936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01138121,"about_ca_topic_score_gemma":0.01707619,"domain_scores_codex":[0.9998577,0.00001925342,0.0000102324,0.00004672894,0.00003834339,0.000027658],"domain_scores_gemma":[0.9998274,0.00005438538,0.00002005005,0.0000163208,0.00006939755,0.00001251392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007183938,0.0008142371,0.01185484,0.000338532,0.0003796196,0.0003907442,0.00007764642,0.3283479,0.02674379,0.002563585,0.01597364,0.6117972],"study_design_scores_gemma":[0.00001234052,0.000120178,0.002225955,0.00001197738,0.00003131152,0.00005802274,0.00001625795,0.9898424,0.005356773,0.0007047929,0.001608331,0.00001178663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.498503,0.003663826,0.4662936,0.001033443,0.0008243832,0.0003156721,0.002758735,0.01054559,0.01606175],"genre_scores_gemma":[0.8740004,0.0006431639,0.1079158,0.0004479969,0.0001062868,0.0001770994,0.003305693,0.00006494888,0.01333857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01138121,"threshold_uncertainty_score":0.02262992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528767234434566,"score_gpt":0.2364038720572143,"score_spread":0.2011161997128686,"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."}}