{"id":"W3010958554","doi":"10.1109/tgrs.2020.2974976","title":"Assessment and Validation of AirMOSS P-Band Root-Zone Soil Moisture Products","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Environmental science; Biome; Shrubland; Synthetic aperture radar; Remote sensing; Radar; Boreal; Water content; Taiga; Grassland; Arid; Vegetation (pathology); Geology; Forestry; Habitat; Geography; Ecosystem; Ecology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002038892,0.0001713648,0.0001998865,0.00004883114,0.0003695894,0.00005288567,0.00006689324,0.00008438829,0.000005486752],"category_scores_gemma":[0.00001083969,0.0001419116,0.00003892392,0.0004757834,0.0004530856,0.000209342,0.000005574201,0.0002282388,0.000005636651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000043805,"about_ca_system_score_gemma":0.00002915551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001108475,"about_ca_topic_score_gemma":0.0005473903,"domain_scores_codex":[0.99861,0.00005747648,0.0002224083,0.0005136419,0.0003633248,0.0002332132],"domain_scores_gemma":[0.9995107,0.00004541457,0.00009619968,0.0001748778,0.00002651938,0.0001463015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002544498,0.00003167458,0.0001621369,0.00003995223,0.00001133266,0.00001338942,0.001611268,0.003023117,0.2341236,0.000001325568,0.00002994413,0.7609268],"study_design_scores_gemma":[0.0009166487,0.000511884,0.1061538,0.0001984823,0.0001344891,0.0002309146,0.0009857659,0.1168916,0.7725005,0.000170561,0.0006880136,0.0006173316],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7378874,0.00003036465,0.2585437,0.00177097,0.000211156,0.000157899,0.000001707374,0.00003578865,0.001360973],"genre_scores_gemma":[0.9826115,0.00007221715,0.01682145,0.0003059187,0.00004665004,3.000433e-8,8.552465e-7,0.00001200233,0.0001294109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7603095,"threshold_uncertainty_score":0.5786986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376296703296704,"score_gpt":0.2376905618172792,"score_spread":0.2239275947843122,"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."}}