{"id":"W4280533570","doi":"10.18280/ria.360204","title":"Pest Early Detection in Greenhouse Using Machine Learning","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nvidia","keywords":"Greenhouse; PEST analysis; Convolutional neural network; Agricultural engineering; Integrated pest management; Computer science; Pest control; Artificial intelligence; Engineering; Ecology; Agronomy; Biology; Botany","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":[0.0002514353,0.0005417368,0.0003410391,0.000438245,0.0001935345,0.0002934017,0.0004272385,0.0005204193,0.0006658937],"category_scores_gemma":[0.0004830438,0.000189206,0.0003683208,0.0002328475,0.0001989726,0.000529715,0.0002729552,0.0004421053,0.0001867145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007334946,"about_ca_system_score_gemma":0.0004148194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006347794,"about_ca_topic_score_gemma":0.006727873,"domain_scores_codex":[0.9999139,0.00001107701,0.000003229531,0.00003405749,0.0000218153,0.00001587634],"domain_scores_gemma":[0.9997638,0.00009786916,0.00003783242,0.00002163114,0.00006265203,0.00001630464],"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":[0.0002495579,0.0003563055,0.01181611,0.0001370824,0.00009323465,0.0003249931,0.00008334705,0.5120716,0.1108756,0.001647317,0.003010107,0.3593347],"study_design_scores_gemma":[0.000003479137,0.00006650875,0.001601785,0.000004675899,0.000007117429,0.00002356828,0.000007514951,0.9871048,0.0100709,0.0007141961,0.0003888309,0.000006614904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4793811,0.001204447,0.5069884,0.0003602947,0.0001225502,0.00009332682,0.0003873291,0.005908675,0.005553874],"genre_scores_gemma":[0.9361756,0.0001876177,0.06148732,0.00006731055,0.00001476728,0.00004103991,0.0002259209,0.00002076864,0.001779732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006347794,"threshold_uncertainty_score":0.0126217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366228610238284,"score_gpt":0.2333054878620208,"score_spread":0.1966826268381924,"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."}}