{"id":"W4302007631","doi":"10.1093/biosci/biac079","title":"Policy-Oriented Research in Invasion Science: Trends, Status, Gaps, and Lessons","year":2022,"lang":"en","type":"article","venue":"BioScience","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Fundação para a Ciência e a Tecnologia; DST-NRF Centre of Excellence for Invasion Biology; Akademie Věd České Republiky; European Cooperation in Science and Technology","keywords":"Convention on Biological Diversity; Sociocultural evolution; Science policy; Political science; Globalization; Research policy; Diversity (politics); Convention; Environmental policy; Policy development; Regional science; Biodiversity; Environmental resource management; Geography; Ecology; Environmental planning; Public administration; Economics; Biology","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001951993,0.00008085871,0.0000769509,0.000469712,0.001333682,0.00008292132,0.0005069497,0.0000199935,0.01042129],"category_scores_gemma":[0.0001714341,0.0000766942,0.00001490868,0.00758177,0.002266903,0.0003090617,0.001762401,0.0002225984,0.00007999202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001801127,"about_ca_system_score_gemma":0.0001348212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002615391,"about_ca_topic_score_gemma":0.0005937121,"domain_scores_codex":[0.9971206,0.0001099744,0.0001344398,0.0005596156,0.001303107,0.0007722966],"domain_scores_gemma":[0.9994189,0.00003923223,0.00003505278,0.0002613468,0.00001449562,0.0002309968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005902701,0.0006727615,0.3666414,0.00001141677,0.000001038773,0.00004052639,0.003724294,0.00005611542,0.4749757,0.09531972,0.01398465,0.04451332],"study_design_scores_gemma":[0.0003123656,0.0001357354,0.8493842,0.000004886774,6.405481e-7,0.00001491941,0.00749777,0.0002606009,0.002601702,0.0003748779,0.1392582,0.0001540157],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9568415,0.00007022897,0.000002421866,0.004586278,0.0001389872,0.00009975784,0.00008152209,0.00002473318,0.03815455],"genre_scores_gemma":[0.9986899,0.0001660955,0.00003884344,0.0002550004,0.000009781708,0.00003445895,0.000009862473,0.000004057958,0.0007919585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4827429,"threshold_uncertainty_score":0.9999664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1063098487401514,"score_gpt":0.3821004530242826,"score_spread":0.2757906042841312,"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."}}