{"id":"W3206168157","doi":"10.3390/rs13193980","title":"Satellite Retrieval of Microwave Land Surface Emissivity under Clear and Cloudy Skies in China Using Observations from AMSR-E and MODIS","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Environmental science; Moderate-resolution imaging spectroradiometer; Emissivity; Satellite; Remote sensing; Atmospheric radiative transfer codes; Microwave; Atmosphere (unit); Atmospheric sciences; Cloud cover; Brightness temperature; Radiative transfer; Meteorology; Cloud computing; Geology; Physics","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":[0.0002936843,0.0004870704,0.0002921403,0.000935045,0.0002781776,0.0003475187,0.0003804582,0.0002291265,0.0003136125],"category_scores_gemma":[0.0002909154,0.0001867968,0.0003157314,0.001006145,0.0002023494,0.0004272708,0.0003578622,0.0001094071,0.00007703958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007050568,"about_ca_system_score_gemma":0.001166652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09686211,"about_ca_topic_score_gemma":0.09699559,"domain_scores_codex":[0.9998575,0.00001027499,0.00001515473,0.00004833712,0.00003945138,0.00002923313],"domain_scores_gemma":[0.9998602,0.00001074587,0.00003825863,0.00001684813,0.0000474253,0.00002646678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004900168,0.0003164358,0.7711776,0.0003560699,0.0003998179,0.0006691872,0.0007097543,0.07697129,0.07514574,0.0007244505,0.002455824,0.07058385],"study_design_scores_gemma":[0.00006092962,0.00005162658,0.911038,0.00001405016,0.00008904625,0.00005200361,0.000148517,0.08290118,0.004677008,0.0000666356,0.0008746059,0.00002637504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987942,0.00005754208,0.000337777,0.00001170243,0.000003745354,0.000007332838,0.0004503766,0.00002665749,0.0003107137],"genre_scores_gemma":[0.9978466,0.00005640844,0.00063274,0.00001033534,0.000005372154,0.00001024878,0.001153626,0.000003373904,0.0002813043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09686211,"threshold_uncertainty_score":0.1925966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04644136830597307,"score_gpt":0.2372839374330906,"score_spread":0.1908425691271175,"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."}}