{"id":"W2511273674","doi":"10.1016/j.scitotenv.2016.08.153","title":"Scenario analysis of fertilizer management practices for N2O mitigation from corn systems in Canada","year":2016,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs; International Plant Nutrition Institute","keywords":"Fertilizer; Nitrification; Environmental science; Nitrous oxide; Greenhouse gas; Crop yield; Agronomy; Yield (engineering); Agriculture; Agricultural engineering; Nitrogen; Engineering; Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009455326,0.001006435,0.000858505,0.0009811732,0.001496169,0.00176938,0.002080077,0.001423646,0.00296758],"category_scores_gemma":[0.001291358,0.0005290938,0.00142341,0.001679764,0.0009115952,0.0006365557,0.0007882821,0.0008440599,0.0001461678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05240645,"about_ca_system_score_gemma":0.0273426,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9803516,"about_ca_topic_score_gemma":0.9778838,"domain_scores_codex":[0.9990504,0.0002244534,0.00003143273,0.00008303209,0.0001357083,0.0004749405],"domain_scores_gemma":[0.9992525,0.0001541095,0.00007709997,0.00002856257,0.0003080016,0.0001797414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001109953,0.0002602444,0.02829381,0.0001405074,0.0003746497,0.0009410742,0.0001049174,0.9539643,0.001637772,0.005131122,0.003951154,0.004090524],"study_design_scores_gemma":[0.0007066673,0.000664907,0.09119093,0.00006449976,0.0006860155,0.0001511177,0.002551225,0.8922113,0.001917242,0.002618749,0.007045936,0.0001913895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775009,0.0002905094,0.0008667758,0.001128297,0.00003164688,0.000224854,0.007728524,0.0000608669,0.01216753],"genre_scores_gemma":[0.9950225,0.0001765667,0.0006474339,0.00007803022,0.000002492275,0.00005290615,0.001529999,0.00000696122,0.00248313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05240645,"threshold_uncertainty_score":0.3802372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351528056558112,"score_gpt":0.1961567253740814,"score_spread":0.1826414448085003,"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."}}