{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003637344,0.0001623895,0.0001985399,0.0001226375,0.0005523115,0.0001900139,0.000820894,0.0001461877,0.0001756795],"category_scores_gemma":[0.0002221855,0.0001053324,0.00004289514,0.0003317435,0.0004343622,0.0002630958,0.001657667,0.0005113519,0.0006779901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502491,"about_ca_system_score_gemma":0.000006394971,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00721803,"about_ca_topic_score_gemma":0.00247506,"domain_scores_codex":[0.9963061,0.00118661,0.000233636,0.000634052,0.0009367491,0.0007028457],"domain_scores_gemma":[0.9984782,0.0002027493,0.00003778392,0.001081397,0.0000287765,0.0001711069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006904265,0.00009919133,0.0151144,0.00005486602,0.00004338391,0.00003157634,0.007835677,0.07951729,0.2714388,0.00001144054,0.003234777,0.6225496],"study_design_scores_gemma":[0.0002986669,0.00007020412,0.02428401,0.00004237046,0.00001961895,0.00003849357,0.0001952767,0.7138431,0.03249316,0.0007566876,0.2276882,0.0002701656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352584,0.00005003965,0.03169286,0.0006834011,0.0001143762,0.0002184218,0.000001514092,0.0000671563,0.03191385],"genre_scores_gemma":[0.9373376,0.000003637158,0.06049326,0.00007390269,0.0002740951,0.000001259884,0.00004537333,0.00003614491,0.001734745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6343258,"threshold_uncertainty_score":0.999393,"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."}}