{"id":"W2161371786","doi":"10.2136/vzj2014.08.0114","title":"Calibration and Evaluation of a Frequency Domain Reflectometry Sensor for Real‐Time Soil Moisture Monitoring","year":2015,"lang":"en","type":"article","venue":"Vadose Zone Journal","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":120,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Manitoba","funders":"Canadian Space Agency; University of Guelph","keywords":"Water content; Calibration; Environmental science; Soil science; Reflectometry; Moisture; Remote sensing; Hydrology (agriculture); Geology; Geotechnical engineering; Meteorology; Time domain; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001542024,0.0001064536,0.0001546691,0.00007547913,0.0001310211,0.00004442475,0.0000645309,0.00009778291,0.00001919672],"category_scores_gemma":[0.0001461832,0.00008549527,0.00004925675,0.0002021942,0.00006150093,0.0002447356,0.0000311551,0.000143109,0.000005713233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002516357,"about_ca_system_score_gemma":0.00005502504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003891644,"about_ca_topic_score_gemma":0.0001253909,"domain_scores_codex":[0.9986267,0.0001528198,0.0002652625,0.0001576122,0.0006230363,0.0001745373],"domain_scores_gemma":[0.9993894,0.00004852686,0.00020706,0.0001166058,0.00008526856,0.0001531789],"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":[0.0001501961,0.0001084859,0.116844,0.00001893338,0.00007012561,0.00001597502,0.004254329,0.003075579,0.7872831,0.00001750088,0.001965425,0.08619639],"study_design_scores_gemma":[0.008684798,0.001133573,0.8533039,0.0003268114,0.000576101,0.0013104,0.004206434,0.03620985,0.05731443,0.03539702,0.0006613886,0.0008753031],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920951,0.0002185188,0.001951032,0.0002366119,0.000289503,0.000180826,0.000001128697,0.00001467783,0.005012639],"genre_scores_gemma":[0.9665854,0.00004161474,0.03280186,0.00001683356,0.0004103025,0.000001012339,0.000002549982,0.00001501561,0.0001254206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7364599,"threshold_uncertainty_score":0.3486396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03732099200834949,"score_gpt":0.3010071000089638,"score_spread":0.2636861080006143,"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."}}