{"id":"W2783976911","doi":"10.18174/383679","title":"Methodology for estimating emissions from agriculture in the Netherlands. : Calculations of CH4, NH3, N2O, NOx, PM10, PM2.5 and CO2 with the National Emission Model for Agriculture (NEMA)","year":2016,"lang":"en","type":"report","venue":"","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"Rijksinstituut voor Volksgezondheid en Milieu; Rijksdienst voor Ondernemend Nederland","keywords":"Environmental science; Emission inventory; Manure management; Greenhouse gas; NOx; Manure; Agriculture; Compost; Environmental engineering; Particulates; Fertilizer; Pollutant; Agronomy; Waste management; Combustion; Engineering; Chemistry; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000953484,0.0004097495,0.0006798445,0.000088909,0.0002526066,0.00003417938,0.0004825895,0.0009141036,0.00002127646],"category_scores_gemma":[0.002860871,0.0001450054,0.0002154474,0.0002012595,0.00009872921,0.00007183495,0.0001051495,0.0005601707,2.038598e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009896611,"about_ca_system_score_gemma":0.0002319607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007210612,"about_ca_topic_score_gemma":0.00007691611,"domain_scores_codex":[0.9979692,0.00006431633,0.0005771873,0.0004839904,0.0005701956,0.0003351544],"domain_scores_gemma":[0.9945489,0.003994287,0.0004174367,0.0002952107,0.0006738448,0.00007027887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002485011,0.0002016014,0.0001636696,0.0007396691,0.0006776989,0.000002649036,0.001665954,0.09010433,0.2571314,0.003205558,0.6374443,0.008414653],"study_design_scores_gemma":[0.003994683,0.0001606475,0.0002717948,0.0018991,0.000797302,0.00008321833,0.001984484,0.8659285,0.01376343,0.01220162,0.09778643,0.001128782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001765239,0.001264281,0.9728878,0.01373568,0.0001869055,0.00213648,0.001356016,0.0002412474,0.006426325],"genre_scores_gemma":[0.2457465,0.0008033721,0.6885794,0.0005881757,0.002637282,0.003680617,0.003557596,0.0002313579,0.05417569],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7758242,"threshold_uncertainty_score":0.7050404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0952186672489786,"score_gpt":0.3435401900172221,"score_spread":0.2483215227682435,"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."}}