{"id":"W4407724806","doi":"10.1029/2024jd041962","title":"Modeling the Impact of the Bidirectional Exchange of NH <sub>3</sub> From the Great Lakes on a Regional and Local Scale Using GEM‐MACH","year":2025,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Toronto","funders":"Environment and Climate Change Canada","keywords":"Scale (ratio); Environmental science; Mach number; Aerospace engineering; Geography; Engineering; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003684266,0.00046363,0.0003042395,0.0002509161,0.0003312199,0.0006628493,0.0006700714,0.000845986,0.0009037877],"category_scores_gemma":[0.0006387432,0.0003706035,0.0006938442,0.0003826406,0.0004123562,0.0005622424,0.0004684343,0.0004133789,0.00009028573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001185274,"about_ca_system_score_gemma":0.0008790763,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1097159,"about_ca_topic_score_gemma":0.06750403,"domain_scores_codex":[0.9999079,0.00002877293,0.00000540779,0.00002822376,0.00001004899,0.00001976449],"domain_scores_gemma":[0.9997681,0.0001099172,0.00003350496,0.00002123543,0.00003126411,0.00003610705],"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":[0.00009306937,0.00006183695,0.02874735,0.00001799963,0.00007148307,0.00008366237,0.00002770715,0.9667096,0.001887221,0.0004085916,0.0003217037,0.001569795],"study_design_scores_gemma":[0.0000198133,0.00002150328,0.007126687,0.000001188693,0.00001384748,0.000005606482,0.00002428223,0.9921573,0.000348962,0.00009520059,0.0001789419,0.000006649714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969138,0.00003907508,0.001206483,0.0001120867,0.00001223792,0.000007326631,0.0004836614,0.00008964854,0.001135667],"genre_scores_gemma":[0.9984218,0.00002571466,0.000952443,0.0000214113,0.000004733696,0.000006586711,0.0003186766,0.00001270862,0.0002358906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8902841,"threshold_uncertainty_score":0.2181546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02885224583963899,"score_gpt":0.2965481736158261,"score_spread":0.2676959277761871,"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."}}