{"id":"W4280587318","doi":"10.3390/insects13050465","title":"Optimization of a Mass Trapping Method against the Striped Cucumber Beetle Acalymma vittatum in Organic Cucurbit Fields","year":2022,"lang":"en","type":"article","venue":"Insects","topic":"Insect-Plant Interactions and Control","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut de Recherche et de Développement en Agroenvironnement; Centre de Recherche Industrielle du Québec; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation; Université du Québec à Montréal","funders":"","keywords":"Semiochemical; Trapping; Biology; Trap (plumbing); Pesticide; Horticulture; Toxicology; Agronomy; Biological system; PEST analysis; Ecology; Environmental science; Environmental engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002595382,0.00008246075,0.0001307128,0.00002251625,0.000216852,0.00002485425,0.0002052931,0.00005084209,0.00178276],"category_scores_gemma":[0.00003376429,0.00003327331,0.00005853884,0.0004852968,0.00001285356,0.000069227,0.00004930353,0.0002506747,0.000003345481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003778641,"about_ca_system_score_gemma":0.00001806551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008056666,"about_ca_topic_score_gemma":0.0008106915,"domain_scores_codex":[0.9990969,0.0002105273,0.0002095042,0.000157325,0.0001593151,0.0001664097],"domain_scores_gemma":[0.9995335,0.0002547624,0.0001005728,0.00005442042,0.00003399614,0.0000227267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001202362,0.0001599354,0.0006937871,0.000007710723,0.00003102296,0.00001765827,0.0006562169,0.02985463,0.9296215,0.0002431516,0.000516225,0.03807797],"study_design_scores_gemma":[0.004851812,0.00314845,0.04956313,0.0002433333,0.0001744181,0.0002380755,0.01443879,0.6980417,0.09934676,0.003290909,0.1246039,0.002058774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935275,0.000103297,0.0008379087,0.001343021,0.000281005,0.0002466034,0.00003652468,0.00002642361,0.003597657],"genre_scores_gemma":[0.9987487,0.00001886664,0.0001391815,0.0006262299,0.00007496429,0.00005074752,0.00003369173,0.000001115531,0.0003064971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8302747,"threshold_uncertainty_score":0.9991298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374871048932267,"score_gpt":0.2274906757098669,"score_spread":0.2137419652205443,"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."}}