{"id":"W2038508132","doi":"10.1029/2004jd005187","title":"Development and evaluation of a sampling system to determine gaseous Mercury fluxes using an aerodynamic micrometeorological gradient method","year":2005,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Rowan Williams Davies & Irwin (Canada); Mohawk College; Agriculture and Agri-Food Canada; University of Guelph; Health Canada","funders":"","keywords":"Flux (metallurgy); Environmental science; Mercury (programming language); Sampling (signal processing); Potential gradient; Atmospheric sciences; Aerodynamics; Gradient method; Meteorology; Physics; Chemistry; Mechanics; Optics","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":[0.002292442,0.000553238,0.0004709548,0.0008656015,0.0004266831,0.0005648082,0.0009743622,0.0006940815,0.0007013649],"category_scores_gemma":[0.001735794,0.000439612,0.0002186491,0.0004137421,0.0003322987,0.0005704568,0.0004584875,0.0004923994,0.0004520426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005055862,"about_ca_system_score_gemma":0.001159889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003887407,"about_ca_topic_score_gemma":0.007655949,"domain_scores_codex":[0.9987763,0.0001820804,0.00006636458,0.0002552608,0.0006619206,0.00005816849],"domain_scores_gemma":[0.9991345,0.0002186935,0.00007922729,0.00008049366,0.000424704,0.00006245456],"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":[0.0002583302,0.000304577,0.01643866,0.0001820423,0.00003654734,0.00006207219,0.0001477823,0.001973792,0.9036519,0.0008152372,0.0006624138,0.07546666],"study_design_scores_gemma":[0.0001768984,0.002579561,0.05283573,0.00004768645,0.0001180262,0.0005471668,0.0001320752,0.09233751,0.8350897,0.0003255621,0.01570069,0.0001093594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3057984,0.0007321241,0.6861365,0.0002670689,0.0001113907,0.001797868,0.0008729378,0.002089268,0.002194377],"genre_scores_gemma":[0.2379961,0.0003900251,0.7575217,0.000158442,0.0000466813,0.001130217,0.0005990568,0.0001101752,0.002047605],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003887407,"threshold_uncertainty_score":0.0121237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08022760475051242,"score_gpt":0.3633288046548122,"score_spread":0.2831011999042997,"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."}}