{"id":"W2167461326","doi":"10.1002/2013wr014127","title":"Root‐zone soil moisture estimation using data‐driven methods","year":2014,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Ontario Innovation Trust","keywords":"Water content; Environmental science; Soil science; Pedotransfer function; DNS root zone; Soil water; Moisture; Forcing (mathematics); Hydrology (agriculture); Hydraulic conductivity; Atmospheric sciences; Geology; Meteorology; Geotechnical engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000566536,0.0004318163,0.0002812889,0.000533159,0.000152211,0.0004343454,0.0005346192,0.0003763486,0.000691826],"category_scores_gemma":[0.001783664,0.0003600555,0.000368084,0.0004054184,0.0001292008,0.0004063238,0.0003442199,0.0004698575,0.0001647108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004801787,"about_ca_system_score_gemma":0.0004697577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006339435,"about_ca_topic_score_gemma":0.006603561,"domain_scores_codex":[0.9998518,0.00005020948,0.000007937841,0.00004427076,0.00003675208,0.000008978246],"domain_scores_gemma":[0.9992296,0.0004174282,0.00008257163,0.00006136894,0.0001877522,0.00002141352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005992167,0.00005398612,0.004885552,0.00004632074,0.00004870212,0.00002123329,0.00001772641,0.948819,0.003938275,0.0004990873,0.0003211874,0.04128888],"study_design_scores_gemma":[0.000002271159,0.000003362777,0.0004036082,0.000001290675,0.000001178401,0.000001272431,0.000001310398,0.9986904,0.0006529393,0.0001625217,0.00007748518,0.000002366416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2284307,0.0001524116,0.7671981,0.0001158993,0.00002955268,0.00007540527,0.001205231,0.001133571,0.001659176],"genre_scores_gemma":[0.9103854,0.0000502984,0.08787222,0.00002893754,0.00001094197,0.0001002383,0.0009418036,0.00004910148,0.0005610973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006339435,"threshold_uncertainty_score":0.01260507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08952690221014431,"score_gpt":0.3964513195376992,"score_spread":0.3069244173275549,"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."}}