{"id":"W2559182939","doi":"10.5539/enrr.v6n4p116","title":"Does Vegetation Restoration Change Regional Ecohydrological Condition at the Loess Plateau in China?","year":2016,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Food and Agriculture; National Eye Institute; National Aeronautics and Space Administration","keywords":"Ecohydrology; Loess plateau; Environmental science; Vegetation (pathology); Evapotranspiration; Surface runoff; Hydrology (agriculture); Plateau (mathematics); China; Precipitation; Physical geography; Loess; Ecosystem; Soil science; Geology; Ecology; Geography; Geomorphology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003175127,0.000118401,0.0001696343,0.0004954925,0.0002886282,0.0004160249,0.0002243062,0.0003008896,0.0006266793],"category_scores_gemma":[0.0004553717,0.00008152601,0.000259449,0.0005140224,0.0005346477,0.0004078403,0.0002400292,0.0001608972,0.00006500238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006331149,"about_ca_system_score_gemma":0.0005512136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02881911,"about_ca_topic_score_gemma":0.04722069,"domain_scores_codex":[0.9998574,0.00002990004,0.000008829479,0.00003764613,0.0000187845,0.00004732207],"domain_scores_gemma":[0.9997755,0.00002265334,0.00007508235,0.00001806691,0.00004498242,0.0000637932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008923961,0.00004921028,0.9809697,0.000023769,0.00006924636,0.0004298368,0.0008039352,0.0007473189,0.008784444,0.0001235889,0.0001739287,0.007735827],"study_design_scores_gemma":[0.000001346016,0.00001077354,0.998952,0.000001249978,0.000006353755,0.00001829099,0.0003560667,0.0004636825,0.00007955623,0.00002243999,0.00008613343,0.000002080349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996326,0.00004323361,0.00003348585,0.00006132101,0.000001366275,0.000001597303,0.00003301512,0.000003403786,0.0001900603],"genre_scores_gemma":[0.9998248,0.00002235291,0.0000193523,0.00001224831,0.000002164355,9.338455e-7,0.00004907621,5.770927e-7,0.00006849619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02881911,"threshold_uncertainty_score":0.05730271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730495843406025,"score_gpt":0.2703020807030477,"score_spread":0.2429971222689874,"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."}}