{"id":"W2901109559","doi":"10.1016/j.atmosenv.2018.11.034","title":"A flexible semi-empirical model for estimating ammonia volatilization from field-applied slurry","year":2018,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Slurry; Volatilisation; Ammonia; Environmental science; Field (mathematics); Environmental engineering; Chemistry; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001572014,0.0007248623,0.001272794,0.0003846995,0.0004251828,0.0009938949,0.002498046,0.001927664,0.001105965],"category_scores_gemma":[0.003667596,0.0008898697,0.0009223581,0.0006946162,0.0008494031,0.001219483,0.0009483579,0.00130718,0.0003487387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009708595,"about_ca_system_score_gemma":0.001442132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03608907,"about_ca_topic_score_gemma":0.02133222,"domain_scores_codex":[0.9996403,0.00009639876,0.00002283877,0.0001306163,0.00005783018,0.00005198395],"domain_scores_gemma":[0.9984395,0.001117324,0.0001481718,0.00009456929,0.0001587604,0.0000416878],"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":[0.0000349724,0.00001752026,0.0004655464,0.00001634813,0.00001693949,0.00001986071,0.00001047377,0.9942562,0.0005165508,0.0005838732,0.000076752,0.003984974],"study_design_scores_gemma":[0.000003333849,0.000004055443,0.00009192925,6.197441e-7,0.000002082139,0.000002084048,0.000001043157,0.9996144,0.00006896229,0.0001853207,0.00002404612,0.000002110183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1502621,0.000293101,0.8468492,0.0002328985,0.00003912167,0.00004903435,0.0004342454,0.0007427286,0.001097694],"genre_scores_gemma":[0.9584449,0.000137632,0.03747304,0.00007082998,0.00003047434,0.0001708221,0.0005573762,0.00007396496,0.003040916],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03608907,"threshold_uncertainty_score":0.07175797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607617285671691,"score_gpt":0.2443252533387522,"score_spread":0.2282490804820352,"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."}}