{"id":"W2763409194","doi":"10.1175/jhm-d-17-0062.1","title":"Turbulent Heat Fluxes during an Extreme Lake-Effect Snow Event","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"College of Engineering, Michigan State University; University of Michigan; National Oceanic and Atmospheric Administration; U.S. Environmental Protection Agency","keywords":"Environmental science; Latent heat; Sensible heat; Climatology; Turbulence; Meteorology; Snow; Climate model; Flux (metallurgy); Atmospheric sciences; Atmosphere (unit); Heat flux; Numerical weather prediction; Evaporation; Boundary layer; Climate change; Geology; Heat transfer; Geography; Mechanics","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":[0.0002351154,0.0003525329,0.0003271991,0.0003434214,0.0006436623,0.0005355222,0.0002017636,0.0005004916,0.0005854105],"category_scores_gemma":[0.0004739492,0.0001920293,0.000309162,0.0002680258,0.0003580482,0.000463645,0.0004230336,0.0003668796,0.00007914219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000916315,"about_ca_system_score_gemma":0.0004607973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02329572,"about_ca_topic_score_gemma":0.02287359,"domain_scores_codex":[0.9999207,0.00001255455,0.000006745567,0.00001721802,0.00001626504,0.00002646944],"domain_scores_gemma":[0.9998637,0.0000435164,0.00001917533,0.000008476458,0.00003197731,0.00003305991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002289777,0.000738442,0.5415002,0.0001134828,0.0003656139,0.002409448,0.001080297,0.3469648,0.0911838,0.00134335,0.002177565,0.009833324],"study_design_scores_gemma":[0.000139241,0.000318956,0.5128447,0.00001426604,0.00005381336,0.00007736924,0.0004881211,0.4733102,0.01167572,0.0003359123,0.0006971731,0.00004441086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994115,0.0000063049,0.0001361463,0.00002080319,0.000004910298,0.000004386092,0.0001192602,0.00002498259,0.0002718039],"genre_scores_gemma":[0.9996755,0.000005447665,0.00008445016,0.000003086243,0.000002367266,0.000002965727,0.0001645929,0.000002968659,0.0000585968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02329572,"threshold_uncertainty_score":0.04632026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204303284976799,"score_gpt":0.2651752616269732,"score_spread":0.2331322287772052,"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."}}