{"id":"W2944636030","doi":"10.2134/jeq2018.12.0433","title":"Assessing the Impacts of Climate Variability on Fertilizer Management Decisions for Reducing Nitrogen Losses from Corn Silage Production","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; McGill University; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Environmental science; Fertilizer; Leaching (pedology); Manure; Ammonia volatilization from urea; Agronomy; Drainage; Silage; Tile drainage; Tonne; Surface runoff; Soil water; Engineering; Waste management; Soil science; Ecology","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":[0.002256424,0.000162775,0.0002859293,0.00003276773,0.0001498371,0.0000440952,0.0002929343,0.00005869107,0.0002039023],"category_scores_gemma":[0.0001476399,0.0001061843,0.0002080819,0.0000875296,0.0001722762,0.0004594217,0.0001913792,0.0001713598,0.00003840759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000399904,"about_ca_system_score_gemma":0.00000656199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000454261,"about_ca_topic_score_gemma":0.000001591897,"domain_scores_codex":[0.9978198,0.0002701938,0.000767254,0.0002972232,0.0005978876,0.0002476107],"domain_scores_gemma":[0.9982319,0.0005028834,0.000714278,0.000456802,0.000007028868,0.00008707079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004060827,0.0007064668,0.9645151,0.00002754183,0.00006544132,0.000001992302,0.0003459615,0.002094882,0.02334979,0.00002824827,0.00006561733,0.008392874],"study_design_scores_gemma":[0.0006945634,0.00021018,0.9758257,0.0001015577,0.00008981548,0.00000674764,0.0009473346,0.000302262,0.0105363,0.01092087,0.0002205916,0.0001440935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980175,0.00002309911,0.0004000732,0.000195117,0.0004347542,0.0004397244,0.00006462783,0.000005593847,0.0004195202],"genre_scores_gemma":[0.9974844,0.0001221012,0.002188837,0.00008917423,0.00006243621,0.00000487044,0.0000107159,0.00001472512,0.00002266938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01281349,"threshold_uncertainty_score":0.4330071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521318562737219,"score_gpt":0.3036691983790517,"score_spread":0.2784560127516795,"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."}}