{"id":"W2995210602","doi":"10.1139/er-2019-0024","title":"Challenges and opportunities in developing decision support systems for risk assessment and management of forest invasive alien species","year":2019,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Decision support system; Environmental resource management; Risk assessment; Risk management; Risk analysis (engineering); Business; Environmental planning; Computer science; Ecology; Geography; Biology; Environmental science; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008761071,0.0001733123,0.0003496764,0.00005174076,0.00005679899,0.00001232977,0.0001323943,0.00005114123,0.000141402],"category_scores_gemma":[0.00000711159,0.0001478338,0.00004084641,0.00002917098,0.0001602896,0.0001943588,0.0004027367,0.00005915137,0.00005241131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000187547,"about_ca_system_score_gemma":0.000004028199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001840368,"about_ca_topic_score_gemma":0.0002229394,"domain_scores_codex":[0.99875,0.00008361907,0.0004239318,0.0003636412,0.0001663307,0.0002124843],"domain_scores_gemma":[0.9993851,0.0001171382,0.00022035,0.0002241497,4.465842e-7,0.00005282346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007109143,0.0002361856,0.5831074,0.001483715,0.0001014081,0.00003052008,0.001173306,0.0002497358,0.0002073713,0.01928818,0.00133352,0.3927176],"study_design_scores_gemma":[0.0005142727,0.0001937247,0.7842138,0.0002275899,0.00003152575,0.000006011098,0.001081701,0.0001051884,0.00001312359,0.0005577692,0.2128997,0.0001555977],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709958,0.01495962,0.0004635739,0.0001198786,0.0001525736,0.002757983,0.00001146142,0.000007102547,0.01053204],"genre_scores_gemma":[0.5195961,0.4764019,0.003067539,0.00007179531,0.000004630305,0.0002071407,0.00001306023,0.000009144907,0.0006286806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4614423,"threshold_uncertainty_score":0.6028487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06683181611485403,"score_gpt":0.2799021356708749,"score_spread":0.2130703195560208,"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."}}