{"id":"W2109317186","doi":"10.1016/j.biosystemseng.2006.08.002","title":"Surface Irrigation of Dairy Farm Effluent, Part I: Nutrient and Bacterial Load","year":2006,"lang":"en","type":"article","venue":"Biosystems Engineering","topic":"Wastewater Treatment and Reuse","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Manure; Environmental science; Effluent; Surface runoff; Septic tank; Nutrient; Manure management; Irrigation; Nutrient management; Wastewater; Environmental engineering; Animal science; Agronomy; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000338153,0.0003511603,0.0006620355,0.0002470237,0.00032062,0.0008254569,0.0002979454,0.0007107239,0.001428433],"category_scores_gemma":[0.0008142855,0.0002353945,0.0003782241,0.0005420325,0.0004416418,0.0005470849,0.000373375,0.0004271971,0.0003262945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009422402,"about_ca_system_score_gemma":0.0007827829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007701523,"about_ca_topic_score_gemma":0.008745029,"domain_scores_codex":[0.9996278,0.00008887549,0.00003214942,0.00007271905,0.0001132809,0.00006501668],"domain_scores_gemma":[0.9995534,0.0001741479,0.00009227541,0.00003631892,0.0001059686,0.00003794003],"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":[0.005482081,0.0004744364,0.06557286,0.0002993421,0.0001110131,0.0001639356,0.0003749067,0.001921965,0.8877074,0.00020789,0.0007280396,0.03695624],"study_design_scores_gemma":[0.0000940205,0.004223286,0.477232,0.00003863148,0.0001591534,0.0003613708,0.0007305351,0.00858207,0.5040457,0.0007356828,0.003748347,0.00004906538],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968714,0.000716859,0.001064421,0.00004992508,0.000008948307,0.00001777955,0.0002017357,0.00001306403,0.001055834],"genre_scores_gemma":[0.9952059,0.0005378021,0.0006744526,0.00005070058,0.000009138371,0.00002098848,0.0004917198,0.00001671644,0.002992574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007701523,"threshold_uncertainty_score":0.01531339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005388472174539113,"score_gpt":0.1674524012709611,"score_spread":0.1620639290964219,"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."}}