{"id":"W3088057135","doi":"10.1093/jee/toaa181","title":"Maximizing Bark and Ambrosia Beetle (Coleoptera: Curculionidae) Catches in Trapping Surveys for Longhorn and Jewel Beetles","year":2020,"lang":"en","type":"article","venue":"Journal of Economic Entomology","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Natural Resources Canada; Canadian Food Inspection Agency; Ministry of Natural Resources","keywords":"Longhorn beetle; Biology; Understory; Curculionidae; Ambrosia beetle; Ambrosia; Bark (sound); Buprestidae; Hardwood; Canopy; Botany; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006826688,0.0000946938,0.0002494991,0.00006496302,0.00005364938,0.00001875595,0.0001133433,0.00007210162,0.0001584818],"category_scores_gemma":[0.00005837377,0.00009292721,0.00004152902,0.00003870559,0.0001461087,0.0001890882,0.00009863107,0.0001175909,0.00001433373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009179924,"about_ca_system_score_gemma":0.00001238204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001454613,"about_ca_topic_score_gemma":0.00141999,"domain_scores_codex":[0.999176,0.00008703476,0.0003435833,0.0001787094,0.00002821236,0.0001864759],"domain_scores_gemma":[0.9995356,0.0001271239,0.0001872636,0.00004903126,0.00000560175,0.00009540754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003315591,0.0001344615,0.960974,0.000110535,0.000165979,0.0001158527,0.003170891,0.008685314,0.01004379,0.002403083,0.003682906,0.01018157],"study_design_scores_gemma":[0.001145719,0.0003924423,0.9917511,0.00001039481,0.00002210546,0.00007197629,0.0002163108,0.001553647,0.0002237252,0.002115456,0.002380916,0.0001161998],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973536,0.0002264813,0.0007388799,0.0006558274,0.000215433,0.0001477102,0.000002516092,0.000003858702,0.0006556669],"genre_scores_gemma":[0.998369,0.000180909,0.0008569763,0.0004709613,0.00006987357,0.000006967887,0.000001002145,0.000007001212,0.00003733559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03077705,"threshold_uncertainty_score":0.3789462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140847318595101,"score_gpt":0.2400707101944932,"score_spread":0.2186622370085422,"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."}}