{"id":"W4400340071","doi":"10.5194/hess-28-2949-2024","title":"High-resolution long-term average groundwater recharge in Africa estimated using random forest regression and residual interpolation","year":2024,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Economic and Social Research Council; Foreign, Commonwealth and Development Office; Sight Research UK; British Geological Survey; Canadian Institute for Advanced Research","keywords":"Groundwater recharge; Evapotranspiration; Environmental science; Hydrology (agriculture); Hydrogeology; Groundwater; Normalized Difference Vegetation Index; Aridity index; Kriging; Spatial variability; Residual; Soil science; Climate change; Geology; Aquifer; Statistics; Mathematics; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001345799,0.0005066741,0.0004788209,0.0007714509,0.0002520898,0.0004580921,0.0006798808,0.0005009985,0.0006731122],"category_scores_gemma":[0.002543664,0.0003139075,0.001082117,0.001197564,0.0001934982,0.0005448909,0.0002554883,0.0004176861,0.0002496225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006973729,"about_ca_system_score_gemma":0.0007799337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06960244,"about_ca_topic_score_gemma":0.05134645,"domain_scores_codex":[0.9997293,0.0001166677,0.00001641312,0.0000745502,0.00002528762,0.0000377645],"domain_scores_gemma":[0.9993058,0.0003422509,0.0001014568,0.00007503435,0.0001547225,0.00002065766],"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":[0.0001548359,0.00007457309,0.06496875,0.0001082481,0.0002398152,0.0001987516,0.00009568712,0.8912882,0.003699924,0.0005489244,0.0005010138,0.03812119],"study_design_scores_gemma":[0.00001155634,0.0000143818,0.01232176,0.00001326701,0.00002088652,0.00001947172,0.00002260918,0.9865384,0.0006076692,0.0001479335,0.000266561,0.00001542924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9559394,0.000333471,0.0413507,0.000100021,0.00001478611,0.0000190186,0.0009356182,0.000670143,0.0006368143],"genre_scores_gemma":[0.9814056,0.00006325477,0.01762231,0.000007480503,0.000004751714,0.00001242377,0.0007021588,0.00002788732,0.0001541678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06960244,"threshold_uncertainty_score":0.1383946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02899485696636941,"score_gpt":0.2552583866690926,"score_spread":0.2262635297027231,"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."}}