{"id":"W4316193714","doi":"10.1029/2022jd037219","title":"Bulk Transfer Coefficients Estimated From Eddy‐Covariance Measurements Over Lakes and Reservoirs","year":2023,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Russian Science Foundation; Fundação da Universidade Federal do Paraná; Deutsche Forschungsgemeinschaft","keywords":"Eddy covariance; Covariance; Environmental science; Hydrology (agriculture); Geology; Mathematics; Statistics; Ecosystem; Geotechnical engineering","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":[0.0003557383,0.0002839556,0.0003345576,0.0006585277,0.0002706995,0.0004506969,0.0001822887,0.0001800362,0.0003951757],"category_scores_gemma":[0.0009626696,0.0002038199,0.0002110361,0.0006476784,0.000179035,0.0007247298,0.0002885184,0.0001730765,0.00009694164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002947688,"about_ca_system_score_gemma":0.0002873988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00867839,"about_ca_topic_score_gemma":0.01007042,"domain_scores_codex":[0.9998777,0.00001662367,0.000009788409,0.00003091518,0.00004747419,0.00001750827],"domain_scores_gemma":[0.9996517,0.0001216673,0.00006015068,0.00001957402,0.0001331562,0.00001377879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004422912,0.0001341019,0.4761996,0.0002969168,0.000301388,0.0002143837,0.0006505496,0.03086821,0.4372344,0.0004052307,0.0004814182,0.05277146],"study_design_scores_gemma":[0.00001842867,0.0001004005,0.8483368,0.0000210568,0.00008609239,0.00005935003,0.000170987,0.1081099,0.04231575,0.0002121658,0.0005153458,0.00005368199],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976978,0.00004740864,0.001804207,0.000004756998,0.000001857333,0.000005353285,0.0001521699,0.00002661287,0.0002598653],"genre_scores_gemma":[0.998633,0.00003794107,0.0009985085,0.00000235736,0.00000155254,0.000009989475,0.0001966244,0.00000759944,0.0001124966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00867839,"threshold_uncertainty_score":0.01725572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0681764275627166,"score_gpt":0.3291522793334326,"score_spread":0.260975851770716,"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."}}