{"id":"W2505076512","doi":"10.1175/jamc-d-16-0143.1","title":"The Observation Record Length Necessary to Generate Robust Soil Moisture Percentiles","year":2016,"lang":"en","type":"article","venue":"Journal of Applied Meteorology and Climatology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Water content; Percentile; Moisture; Soil science; Hydrology (agriculture); Geology; Statistics; Meteorology; Geography; Mathematics; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0005326453,0.0001316494,0.0002749797,0.00003926578,0.000270908,0.00001629223,0.0001891556,0.0001840547,0.00004000136],"category_scores_gemma":[0.00005941727,0.00006490797,0.00005638169,0.00009581049,0.0003113387,0.00008144217,0.000110226,0.0002043474,0.00004345129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003813182,"about_ca_system_score_gemma":0.00001407778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002517408,"about_ca_topic_score_gemma":0.0008128086,"domain_scores_codex":[0.9989111,0.00009628468,0.0003793239,0.0001948104,0.0001270271,0.0002914135],"domain_scores_gemma":[0.9991441,0.0003058944,0.0002678873,0.0001510922,0.00002426278,0.0001067632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001687891,0.00008687659,0.1541859,0.00001143871,0.0001764751,0.00008992042,0.0009611089,0.0006384915,0.1460582,0.003702375,0.01710247,0.6752989],"study_design_scores_gemma":[0.002082981,0.000657506,0.8477804,0.00003196298,0.000214652,0.001451723,0.001236274,0.0001659781,0.007879725,0.01734805,0.1207195,0.0004312414],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823638,0.0001728728,0.0008474835,0.01052401,0.0005374359,0.00008130095,4.513548e-7,0.000008873776,0.005463808],"genre_scores_gemma":[0.9932573,0.0009162742,0.003533775,0.001987563,0.0001525693,0.000001353232,4.788972e-7,0.00001112459,0.0001395002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6935945,"threshold_uncertainty_score":0.264687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01279148456648044,"score_gpt":0.2169761851067382,"score_spread":0.2041847005402578,"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."}}