{"id":"W244442257","doi":"","title":"Outlook for ash in your forest: results of emerald ash borer research and implications for management","year":2014,"lang":"en","type":"article","venue":"","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emerald ash borer; Wood ash; Emerald; Fraxinus; Fly ash; Forestry; White (mutation); Logging; Environmental science; Archaeology; Geography; Agroforestry; Ecology; Engineering; Waste management; Biology; Geology; Mineralogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002002949,0.0003805825,0.0001741339,0.0008572948,0.0007799389,0.001815493,0.0004837455,0.001094591,0.009449184],"category_scores_gemma":[0.001977463,0.00007323152,0.0003792707,0.001241329,0.0003202589,0.00138288,0.0004191112,0.0009058011,0.001460675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580907,"about_ca_system_score_gemma":0.002406646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03320072,"about_ca_topic_score_gemma":0.08211279,"domain_scores_codex":[0.9994746,0.0001400063,0.00003062432,0.00004356505,0.0002085964,0.0001026338],"domain_scores_gemma":[0.9974515,0.0003877425,0.0003065196,0.0000482833,0.001051758,0.0007541773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000806315,0.000659554,0.2404423,0.001104405,0.00009023975,0.00061419,0.0007425487,0.0005743781,0.001386745,0.003210635,0.2306117,0.519757],"study_design_scores_gemma":[0.00007800401,0.001293647,0.637713,0.001649154,0.000314446,0.0007199929,0.0146159,0.0008387488,0.001590894,0.003580573,0.3375262,0.00007944379],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.348846,0.2992137,0.001822393,0.2100173,0.00523648,0.0001690478,0.02041022,0.0003851158,0.1138998],"genre_scores_gemma":[0.715533,0.2187912,0.006091226,0.01652461,0.002153342,0.0001402492,0.00987853,0.00004943747,0.03083838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03320072,"threshold_uncertainty_score":0.06601495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04883520104733629,"score_gpt":0.3380129664655577,"score_spread":0.2891777654182214,"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."}}