{"id":"W4368232969","doi":"10.1109/lgrs.2023.3272878","title":"Performance of SMOS Soil Moisture Products Over Core Validation Sites","year":2023,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"California Institute of Technology; National Aeronautics and Space Administration","keywords":"Radiometer; Environmental science; Anomaly (physics); Remote sensing; Satellite; Mean squared error; Product (mathematics); Meteorology; Mathematics; Statistics; Physics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003667751,0.0001768439,0.0001796796,0.0001015933,0.0003044934,0.00004157372,0.0001293164,0.00007521526,0.000003352957],"category_scores_gemma":[0.00006067907,0.0001423615,0.00004233793,0.0009902165,0.0006521269,0.0002446096,0.0000909825,0.0001527038,0.00005796826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004574668,"about_ca_system_score_gemma":0.00001406305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001316898,"about_ca_topic_score_gemma":0.0001450262,"domain_scores_codex":[0.9983856,0.00003326918,0.0002188675,0.0004903809,0.0004744324,0.0003974403],"domain_scores_gemma":[0.9994311,0.00004925086,0.0001305317,0.0002936985,0.00002004765,0.00007532712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000009837794,0.000004943954,0.009719338,0.00003179342,0.000004301887,0.00001904472,0.0007273057,0.001495594,0.8767583,2.818814e-7,0.002632279,0.1085969],"study_design_scores_gemma":[0.0002882655,0.00007775878,0.6389722,0.0001552786,0.00003300762,0.0001096417,0.0001391458,0.1388974,0.2197266,0.00005605656,0.001128493,0.0004160976],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964017,0.00001300929,0.0001961096,0.001654499,0.0005921919,0.0001430822,8.890023e-7,0.00008832714,0.0009102242],"genre_scores_gemma":[0.9951881,0.00005563748,0.003059065,0.001063854,0.0001384175,2.098129e-8,0.000006806403,0.00001522775,0.0004728923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6570318,"threshold_uncertainty_score":0.5805334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01731871592145772,"score_gpt":0.2272298816328595,"score_spread":0.2099111657114017,"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."}}