{"id":"W2129442773","doi":"10.1002/2014wr016534","title":"Global sensitivity analysis of the radiative transfer model","year":2015,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Water content; Radiative transfer; Environmental science; Vegetation (pathology); Precipitation; Sensitivity (control systems); Soil science; Atmospheric radiative transfer codes; Moisture; Atmospheric sciences; Meteorology; Geography; Physics; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002130641,0.0007986675,0.0004554136,0.000921691,0.0003789524,0.0009306924,0.0004609065,0.0006435552,0.001402842],"category_scores_gemma":[0.005613205,0.0002950195,0.001274655,0.0005166102,0.0005340371,0.0006443338,0.0008786701,0.0007672953,0.00008863878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239236,"about_ca_system_score_gemma":0.0005160224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01538865,"about_ca_topic_score_gemma":0.003481212,"domain_scores_codex":[0.9988775,0.0006971349,0.00002787136,0.0001548814,0.0001296916,0.0001130062],"domain_scores_gemma":[0.9962068,0.003066765,0.0001994711,0.0002481809,0.0002340513,0.00004465695],"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":[0.00003513073,0.00001476192,0.003604279,0.00002009717,0.00009283082,0.0000719329,0.00001934525,0.9903765,0.001411533,0.00223729,0.0002546913,0.001861748],"study_design_scores_gemma":[0.000005927949,0.00003749961,0.002577234,0.000005535778,0.00003347566,0.00002248997,0.00003151039,0.993848,0.001056602,0.002024729,0.000342397,0.00001460453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8612427,0.0004278296,0.1224689,0.0007363644,0.00007234222,0.000131609,0.001133236,0.000524192,0.01326275],"genre_scores_gemma":[0.9973831,0.00003811616,0.001893531,0.0000333133,0.00000648704,0.0000252246,0.0001776603,0.00002246191,0.0004200777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01538865,"threshold_uncertainty_score":0.0305981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06015680150052469,"score_gpt":0.3161232890123344,"score_spread":0.2559664875118097,"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."}}