{"id":"W2012864575","doi":"10.1897/04-268r.1","title":"The use of terrestrial and aquatic microcosms and mesocosms for the ecological risk assessment of veterinary medicinal products","year":2005,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Microcosm; Mesocosm; Environmental science; Ecology; Risk assessment; Environmental chemistry; Biology; Chemistry; Ecosystem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002302417,0.0006350862,0.000760489,0.0006421283,0.0007039241,0.001259582,0.0008569664,0.0008322651,0.0008955038],"category_scores_gemma":[0.002670805,0.0002646238,0.0009054965,0.0006394778,0.001291145,0.001285635,0.001413336,0.0009794711,0.0002110601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238908,"about_ca_system_score_gemma":0.001013603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004068665,"about_ca_topic_score_gemma":0.008892255,"domain_scores_codex":[0.9969151,0.001530851,0.0001942431,0.0006314639,0.0006535288,0.00007485526],"domain_scores_gemma":[0.9966447,0.001651778,0.0007173397,0.0004948342,0.0003477102,0.0001435113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001727977,0.001391533,0.04100936,0.003057651,0.0004903724,0.000591867,0.0006672359,0.02430035,0.7861808,0.007219971,0.001189412,0.1321734],"study_design_scores_gemma":[0.0005393159,0.01777305,0.1498893,0.0005172931,0.001115494,0.002026598,0.00150706,0.08265603,0.6859851,0.01730859,0.04023216,0.0004498978],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8064992,0.01986384,0.1501436,0.001574886,0.000347058,0.002053638,0.002498391,0.0003182519,0.01670115],"genre_scores_gemma":[0.8000392,0.01708262,0.1773361,0.0006403624,0.0001384524,0.001646449,0.001233493,0.00004331643,0.001840009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004068665,"threshold_uncertainty_score":0.01217651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0418288658685758,"score_gpt":0.3020550160684535,"score_spread":0.2602261501998777,"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."}}