{"id":"W4402261444","doi":"10.1109/igarss53475.2024.10642889","title":"Estimating Daily Root Zone Soil Moisture at 30 Meters Spatial Resolution by Assimilating Fused Surface Soil Moisture to a Modified Hydrological Model","year":2024,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Water content; Environmental science; Moisture; Soil science; DNS root zone; Root (linguistics); Hydrology (agriculture); Soil water; Resolution (logic); Remote sensing; Geology; Meteorology; Geotechnical engineering; Geography; Computer science","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":[0.0002599938,0.0003080789,0.0002406326,0.0002376505,0.0001181485,0.0002120001,0.0003433445,0.0002885456,0.0002235423],"category_scores_gemma":[0.000410514,0.0001977893,0.0004023517,0.0002905429,0.0001138656,0.000614815,0.0002974549,0.000309822,0.00006499395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002330765,"about_ca_system_score_gemma":0.0004852102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007842914,"about_ca_topic_score_gemma":0.01050251,"domain_scores_codex":[0.9998883,0.00001728051,0.000006841849,0.00004581131,0.000030445,0.00001144355],"domain_scores_gemma":[0.9999063,0.00002012961,0.00001583757,0.00002559224,0.00002337157,0.000008810531],"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":[0.00008437767,0.0001068137,0.02181397,0.00005325578,0.0001318317,0.0001148309,0.0001106538,0.7864858,0.1043382,0.001304246,0.0003362692,0.08511975],"study_design_scores_gemma":[0.000005410112,0.0000164782,0.005154278,0.000001063609,0.00001244832,0.00001254065,0.000007912052,0.9902313,0.00418143,0.0001921798,0.0001751804,0.000009723521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6407343,0.000105022,0.3572809,0.00005783993,0.00002621155,0.00002107737,0.0002457729,0.0009151209,0.0006137468],"genre_scores_gemma":[0.9236681,0.00004793819,0.07579329,0.00001318998,0.000006045186,0.00001500808,0.0002018031,0.00002752509,0.0002271379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007842914,"threshold_uncertainty_score":0.01559454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547036389568352,"score_gpt":0.2371664618884401,"score_spread":0.2216960979927566,"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."}}