{"id":"W2135469220","doi":"10.1016/j.atmosenv.2012.02.059","title":"Measuring gas emissions from animal waste lagoons with an inverse-dispersion technique","year":2012,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Agricultural Research Service; U.S. Department of Agriculture","keywords":"Berm; Environmental science; Anemometer; Wind speed; Hydrology (agriculture); Atmospheric sciences; Atmospheric dispersion modeling; Meteorology; Soil science; Geology; Air pollution; Geotechnical engineering; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001112463,0.0002618144,0.0002289033,0.000005328221,0.0001262312,0.00001447826,0.0002545616,0.0001904994,0.0009485453],"category_scores_gemma":[0.00003199597,0.0002027578,0.00006584073,0.00009670622,0.00007429149,0.0002627931,0.0001638239,0.000308261,0.00009515353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001853567,"about_ca_system_score_gemma":0.000009121904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009214353,"about_ca_topic_score_gemma":0.000002191126,"domain_scores_codex":[0.998664,0.00002623092,0.000202147,0.0003211487,0.0002983506,0.0004881372],"domain_scores_gemma":[0.9990318,0.00004688459,0.00006835283,0.0005363857,0.000004927027,0.0003116293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008784035,0.0002458623,0.01629654,0.00001214478,0.00005432183,0.00001047401,0.0002680591,0.003541198,0.9728749,0.00007448022,0.0003396414,0.006194566],"study_design_scores_gemma":[0.001972905,0.0006605604,0.005839378,0.0003254265,0.0002383518,0.0000335583,0.004216463,0.06109431,0.8748057,0.0001945211,0.04902415,0.001594694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659943,0.0005597605,0.03094911,0.0002490357,0.00005776306,0.0002651198,0.000007723341,0.0005688071,0.00134836],"genre_scores_gemma":[0.9283935,0.0001208634,0.0708278,0.0000523831,0.0001280451,0.00008847119,0.00001328381,0.00005311981,0.0003225075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09806918,"threshold_uncertainty_score":0.9999647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01641523594957792,"score_gpt":0.1951445970598481,"score_spread":0.1787293611102702,"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."}}