{"id":"W2126707506","doi":"10.1002/2015jd023550","title":"Potential of bias correction for downscaling passive microwave and soil moisture data","year":2015,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Downscaling; Environmental science; Water content; Watershed; Brightness temperature; Moisture; Soil science; Microwave; Atmospheric sciences; Hydrology (agriculture); Remote sensing; Meteorology; Precipitation; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001321747,0.0004271067,0.0002392161,0.0005411408,0.0002661173,0.0004335945,0.0005390173,0.0003398429,0.001173927],"category_scores_gemma":[0.005480122,0.000238813,0.0003043973,0.0008370748,0.000190716,0.0005612206,0.000480667,0.0004101195,0.0003728139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003562932,"about_ca_system_score_gemma":0.0009334374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009433589,"about_ca_topic_score_gemma":0.01250559,"domain_scores_codex":[0.9996135,0.0001027275,0.00002819598,0.00007920151,0.0001288579,0.00004763358],"domain_scores_gemma":[0.9986161,0.0003994113,0.0001555813,0.0002710401,0.0005232228,0.00003465325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006550703,0.000191192,0.06547681,0.0002525574,0.0003407339,0.0002007448,0.0003530038,0.09883089,0.1767539,0.004532542,0.003992475,0.6484201],"study_design_scores_gemma":[0.0001318682,0.0002238145,0.05782265,0.00008676586,0.0001677215,0.0001610517,0.00017038,0.7512227,0.1639815,0.003888715,0.02203435,0.0001086195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.475085,0.0007769545,0.5141583,0.0006935379,0.000401518,0.0001347921,0.0007130661,0.003904663,0.004132134],"genre_scores_gemma":[0.7328454,0.0002088273,0.2632505,0.0001888194,0.00007128475,0.00007033402,0.0008293825,0.0004591433,0.002076361],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009433589,"threshold_uncertainty_score":0.0187574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06514601499211377,"score_gpt":0.3276640049284186,"score_spread":0.2625179899363049,"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."}}