{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002989503,0.0008721727,0.0005946281,0.001604413,0.0003262799,0.0008768769,0.0009274557,0.0007287143,0.0005985044],"category_scores_gemma":[0.004240202,0.0003641033,0.0009926145,0.001234629,0.0004558149,0.001185666,0.0007071219,0.0003936806,0.000528251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006744344,"about_ca_system_score_gemma":0.0006056877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02132087,"about_ca_topic_score_gemma":0.01662874,"domain_scores_codex":[0.9988878,0.0001583195,0.00009055648,0.0003348812,0.0004256175,0.0001029402],"domain_scores_gemma":[0.9984048,0.0003173187,0.0002026515,0.000271238,0.0007148316,0.00008918959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002813848,0.0007452725,0.3169886,0.0004666435,0.001010458,0.0003083512,0.0005439768,0.3908314,0.07056517,0.001456899,0.01200995,0.2022595],"study_design_scores_gemma":[0.0002314185,0.000332431,0.2551737,0.00005087227,0.000110235,0.00008616696,0.0001453941,0.7142513,0.02472072,0.0003388386,0.00446331,0.00009568042],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845685,0.00014624,0.006386952,0.00005505594,0.00004562809,0.00005278862,0.00456033,0.002195352,0.001989132],"genre_scores_gemma":[0.9630497,0.00006365951,0.01651679,0.00006654164,0.00001932384,0.00004937071,0.01916644,0.000288291,0.0007799797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02132087,"threshold_uncertainty_score":0.04239357,"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."}}