{"id":"W3168620725","doi":"10.1111/afe.12457","title":"Optimizing early detection strategies: defining the effective attraction radius of attractants for emerald ash borer <scp> <i>Agrilus planipennis</i> </scp> Fairmaire","year":2021,"lang":"en","type":"article","venue":"Agricultural and Forest Entomology","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Emerald ash borer; Agrilus; Attraction; Fraxinus; Biology; Range (aeronautics); Ecology; Trap (plumbing); Zoology; Environmental science","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":[0.0010085,0.0003132856,0.0002081649,0.0006252424,0.0001656056,0.0004332557,0.0004265218,0.0001890269,0.0003135859],"category_scores_gemma":[0.002831502,0.0001397781,0.0001752446,0.0001714988,0.0002170393,0.000463227,0.0003143537,0.0001505832,0.00007043747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006165516,"about_ca_system_score_gemma":0.0004374213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008739012,"about_ca_topic_score_gemma":0.01728712,"domain_scores_codex":[0.9997651,0.00008191225,0.00001391731,0.00006511342,0.00004400709,0.00003001426],"domain_scores_gemma":[0.9988149,0.0006032698,0.0003573853,0.00003929781,0.0001200472,0.0000650766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004529773,0.0002819646,0.6633229,0.000245951,0.0001350329,0.0001531294,0.0001991249,0.1576603,0.07014219,0.001478266,0.0005861121,0.1053421],"study_design_scores_gemma":[0.00002945078,0.0004935996,0.3508295,0.00003009909,0.00006924853,0.0001794717,0.0002116074,0.6258723,0.0209112,0.000560095,0.0007744622,0.00003904703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636603,0.0003455248,0.03491211,0.00003799151,0.00000247878,0.00004253524,0.00009688703,0.00007282571,0.0008292582],"genre_scores_gemma":[0.9913089,0.00003771292,0.008484828,0.00000879059,8.929818e-7,0.00001274538,0.00004086264,0.000003195108,0.0001019702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008739012,"threshold_uncertainty_score":0.0173763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005985895533546079,"score_gpt":0.2084091779109715,"score_spread":0.2024232823774255,"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."}}