{"id":"W4294316760","doi":"10.1029/2022ef002774","title":"Decomposing Three Decades of Nitrogen Emissions in Canada","year":2022,"lang":"en","type":"article","venue":"Earth s Future","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Agriculture; Population; Per capita; Emission intensity; Environmental science; Agricultural economics; Unit (ring theory); Fossil fuel; Geography; Natural resource economics; Environmental protection; Economics; Ecology; Chemistry; Mathematics; Demography; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001760893,0.0000542223,0.00009431819,0.00001709035,0.0001865453,0.000002563601,0.0001371385,0.00001893653,0.004599848],"category_scores_gemma":[0.00001122198,0.00005175564,0.00001712971,0.0002127874,0.00002017603,0.00004675996,0.0001256332,0.0002062004,0.000007566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002199744,"about_ca_system_score_gemma":0.0002663384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6815984,"about_ca_topic_score_gemma":0.9595433,"domain_scores_codex":[0.9991972,0.00006303324,0.0001545511,0.0001099018,0.0002695037,0.0002058016],"domain_scores_gemma":[0.9996759,0.00003315491,0.00005457505,0.0001206919,0.000001525531,0.0001141251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002067669,0.00002918403,0.9672508,0.00001129426,0.000002556558,0.000013377,0.0008991609,0.005681521,0.0003873167,0.00008537836,0.01199496,0.01362374],"study_design_scores_gemma":[0.0002080277,0.0000390101,0.7944276,0.000008312794,0.000002449731,0.000008493531,0.001321166,0.0008052501,0.0006822326,0.0007968434,0.2016006,0.00009999745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941217,0.0001998432,0.0000187354,0.003882711,0.0001455761,0.00009585045,0.00002382484,0.000005771396,0.001506003],"genre_scores_gemma":[0.9967615,0.000007263128,0.001246105,0.001876894,0.00004208316,0.000004781808,0.000004848686,0.000004809548,0.000051722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2779449,"threshold_uncertainty_score":0.9963101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594899836741114,"score_gpt":0.2504097144959624,"score_spread":0.2344607161285513,"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."}}