{"id":"W2264960077","doi":"10.1002/2015wr017504","title":"On the variability of the Priestley‐Taylor coefficient over water bodies","year":2015,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Biological and Environmental Research; Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Oceanic and Atmospheric Administration; U.S. Department of Agriculture; Princeton University; U.S. Department of Commerce; U.S. Department of Energy; BP; National Science Foundation","keywords":"Advection; Standard deviation; Water vapor; Turbulence; Cutoff; Flux (metallurgy); Sensible heat; Gaussian; Environmental science; Mathematics; Thermodynamics; Meteorology; Atmospheric sciences; Materials science; Physics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.003445785,0.0001085412,0.0001091428,0.00003878796,0.0003160755,0.000076125,0.0007157394,0.00006534305,0.0008627897],"category_scores_gemma":[0.0001303014,0.00003696084,0.00006221811,0.0001397163,0.0009176082,0.00005498121,0.001093418,0.0003610807,0.0005127158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00015425,"about_ca_system_score_gemma":0.000006560637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005281024,"about_ca_topic_score_gemma":0.00007146197,"domain_scores_codex":[0.9971595,0.000672273,0.0002015204,0.0002631483,0.001220833,0.0004826761],"domain_scores_gemma":[0.99898,0.0001865706,0.00002207968,0.0006849414,0.00003768763,0.00008866221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009668822,0.00155648,0.5190625,0.00008990582,0.0001597333,0.00003189279,0.1613755,0.1860815,0.09752053,0.006873232,0.02417761,0.002104306],"study_design_scores_gemma":[0.001247367,0.0006076973,0.04999197,0.00006995059,0.00003489573,0.00002200474,0.001100442,0.08285306,0.172913,0.04722961,0.643293,0.0006370008],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697095,0.000005149043,0.0000224418,0.001975015,0.00006926384,0.0003586576,0.00001342873,0.00001300436,0.02783357],"genre_scores_gemma":[0.9943861,0.000001341741,0.00001320412,0.00007513722,0.00002051245,0.00003066065,0.000005640495,0.0000106797,0.005456745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6191154,"threshold_uncertainty_score":0.9446943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03933214484469749,"score_gpt":0.2760367520447838,"score_spread":0.2367046072000863,"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."}}