{"id":"W4244014941","doi":"10.32920/ryerson.14644098","title":"Assessment of the Subsurface Pathogen Abatement Effects of Nutrient Management Policy in Ontario","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislation; Nutrient; Agriculture; Environmental science; Nutrient management; Environmental planning; Environmental engineering; Business; Environmental protection; Ecology; Biology; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008487517,0.0002189035,0.0002699523,0.0004518933,0.001006703,0.001235377,0.0005108388,0.0004371554,0.002330408],"category_scores_gemma":[0.003766152,0.0001682345,0.000383186,0.001124488,0.0007538642,0.0005051531,0.0006202414,0.0003665375,0.000134443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05534416,"about_ca_system_score_gemma":0.02974114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9780803,"about_ca_topic_score_gemma":0.9852782,"domain_scores_codex":[0.9989203,0.0001914899,0.0000324702,0.00007611932,0.0004082045,0.0003713488],"domain_scores_gemma":[0.9976521,0.0006236889,0.0004434772,0.00007314237,0.0009097687,0.000297774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004205945,0.0007363359,0.7831162,0.0008079275,0.0004322691,0.001756147,0.004795715,0.08683439,0.01551616,0.01457933,0.01010213,0.07711745],"study_design_scores_gemma":[0.0001015705,0.0005461574,0.9533411,0.00005200415,0.0001196953,0.00005567734,0.007398983,0.0242251,0.001843446,0.001618074,0.01065396,0.00004411978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842414,0.0001746549,0.0002850232,0.0006614241,0.000005250615,0.0001089445,0.001120494,0.00001060584,0.01339213],"genre_scores_gemma":[0.9958478,0.0002047388,0.0003119775,0.00005981491,0.000002390297,0.00002637143,0.0003405566,0.000003252299,0.003202989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05534416,"threshold_uncertainty_score":0.4015518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01279941717660641,"score_gpt":0.268769977261607,"score_spread":0.2559705600850005,"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."}}