{"id":"W2194926314","doi":"10.3390/rs71215853","title":"Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems","year":2015,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada; College of Engineering, Michigan State University; Microsoft Research; Beijing Normal University; University of Virginia; Natural Resources Canada; Université Laval; Oak Ridge National Laboratory; Biological and Environmental Research; Canadian Foundation for Climate and Atmospheric Sciences; National Key Research and Development Program of China; Michigan State University; U.S. Department of Energy; National Science Foundation","keywords":"Latent heat; Arid; Satellite; Environmental science; Flux (metallurgy); Ecosystem; Remote sensing; Algorithm; Atmospheric sciences; Computer science; Meteorology; Geology; Geography; Materials science; Physics; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004235694,0.0007719977,0.000581308,0.001513853,0.0006329242,0.001348414,0.0009230971,0.0009492501,0.0006832998],"category_scores_gemma":[0.00753043,0.0003176347,0.000889476,0.0009684238,0.0004984995,0.002182201,0.0007338757,0.0005421359,0.0002436609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151305,"about_ca_system_score_gemma":0.0009321132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01103444,"about_ca_topic_score_gemma":0.009745732,"domain_scores_codex":[0.9990393,0.0002875111,0.0001040647,0.0003141052,0.0001783245,0.00007673461],"domain_scores_gemma":[0.9965839,0.001813502,0.0003721496,0.0004318876,0.0006656242,0.0001328011],"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":[0.001010927,0.0004254302,0.2778689,0.0001886937,0.0005697828,0.00007648755,0.0002258539,0.5684144,0.004691351,0.001523413,0.00148039,0.1435245],"study_design_scores_gemma":[0.00006030276,0.00009944539,0.04134005,0.00002489855,0.00004020732,0.00003890288,0.000112361,0.9548316,0.002290039,0.0006749561,0.0004552686,0.00003197647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552422,0.0007355309,0.04017983,0.0001722528,0.00006136434,0.00007936676,0.0007963474,0.0005749123,0.0021583],"genre_scores_gemma":[0.9784882,0.0001335783,0.01957312,0.00003428964,0.00001277781,0.00004181094,0.001437086,0.00004708522,0.0002320172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01103444,"threshold_uncertainty_score":0.0224008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03415141741736234,"score_gpt":0.2417448128877815,"score_spread":0.2075933954704192,"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."}}