{"id":"W3196913534","doi":"10.1007/s11694-021-01043-0","title":"EM-ERNet for image-based banana disease recognition","year":2021,"lang":"en","type":"article","venue":"Journal of Food Measurement & Characterization","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Normalization (sociology); Computer science; Artificial intelligence; Pattern recognition (psychology); Robustness (evolution); Feature extraction; Biology","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":[0.0004256384,0.0007670245,0.000525953,0.000720623,0.0001944984,0.000484325,0.0008931588,0.000951416,0.009815821],"category_scores_gemma":[0.0006767542,0.0001768065,0.0005247612,0.0005644506,0.0001502103,0.0004861205,0.0007428844,0.0004966389,0.005272806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002156132,"about_ca_system_score_gemma":0.0004255753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001935856,"about_ca_topic_score_gemma":0.003677295,"domain_scores_codex":[0.999782,0.00003421478,0.00001189636,0.00004950619,0.00008408239,0.00003829883],"domain_scores_gemma":[0.9998657,0.0000369849,0.00001153444,0.00002516443,0.00005046147,0.00001026007],"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":[0.0009441461,0.000257447,0.001103245,0.0001671539,0.0001232049,0.0002426878,0.0000297958,0.02423724,0.07931896,0.002127323,0.01771673,0.873732],"study_design_scores_gemma":[0.00004919468,0.0002355944,0.002453158,0.00002371974,0.00004619782,0.0005044169,0.00003963455,0.8925925,0.0867392,0.001939407,0.01534427,0.00003265853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02481864,0.0007589626,0.9545822,0.0001923665,0.0003514111,0.000118912,0.001142195,0.01299335,0.005041915],"genre_scores_gemma":[0.295399,0.0008141607,0.6647386,0.0007823732,0.0002061269,0.0003083943,0.005159213,0.000534961,0.03205719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009815821,"threshold_uncertainty_score":0.03283715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05424216655050481,"score_gpt":0.2094881620134739,"score_spread":0.1552459954629691,"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."}}