{"id":"W2398737921","doi":"10.1021/acs.est.5b01287","title":"Ecological and Landscape Drivers of Neonicotinoid Insecticide Detections and Concentrations in Canada’s Prairie Wetlands","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Insect and Pesticide Research","field":"Agricultural and Biological Sciences","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wetland; Environmental science; Marsh; Neonicotinoid; Ecology; Abiotic component; Ecosystem; Hydrology (agriculture); Biology; Pesticide; Imidacloprid","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":[0.0002071219,0.00006635602,0.0001027656,0.00005510558,0.0001592817,0.00001296331,0.0001554749,0.00006438243,0.00009554951],"category_scores_gemma":[0.00009241799,0.00003179753,0.000007321916,0.000483904,0.0009410359,0.00009085204,0.0001530012,0.0001390128,0.000001612647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001825763,"about_ca_system_score_gemma":0.0001475165,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06853622,"about_ca_topic_score_gemma":0.7467973,"domain_scores_codex":[0.99918,0.00002432977,0.0001213902,0.000213794,0.0001927149,0.0002677751],"domain_scores_gemma":[0.9997284,0.00007266111,0.00003762138,0.00003785981,0.00000861656,0.0001147842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005307893,0.00002513844,0.8702438,5.648719e-7,9.18714e-7,0.000005149373,0.00004381279,0.00001391872,0.1239432,0.0002425399,0.00001421988,0.005461452],"study_design_scores_gemma":[0.0001629209,0.0003193576,0.984304,0.000002843579,0.000002317671,0.00003776092,0.002201376,0.0003457996,0.01135466,0.0005143728,0.0006811934,0.00007341221],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978383,0.0001014636,0.000001367679,0.001370774,0.00003118693,0.0001157844,0.00001115339,0.00001173263,0.0005182456],"genre_scores_gemma":[0.9998325,0.00005166191,0.00005045618,0.00003192536,0.000008460108,0.000007836891,0.000002666219,3.612732e-7,0.00001411152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.678261,"threshold_uncertainty_score":0.9376665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185809713491523,"score_gpt":0.2062540326086126,"score_spread":0.1943959354736974,"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."}}