{"id":"W1994598691","doi":"10.1002/hyp.7470","title":"Hydrological modelling of Ethiopian catchments using limited data","year":2009,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Surface runoff; Calibration; Environmental science; Soil and Water Assessment Tool; Hydrology (agriculture); Hydrological modelling; SWAT model; Streamflow; Statistics; Climatology; Drainage basin; Mathematics; Geology; Ecology; Geography; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009804099,0.0002927805,0.0004251295,0.0005510366,0.0003786047,0.0009843169,0.000705573,0.0005287185,0.0006784798],"category_scores_gemma":[0.002156802,0.0004518752,0.0004242162,0.0007550227,0.0004381784,0.0006854541,0.0005020851,0.0003353025,0.00006725777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266107,"about_ca_system_score_gemma":0.0007700602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01994791,"about_ca_topic_score_gemma":0.01495039,"domain_scores_codex":[0.9997696,0.000125248,0.00001282615,0.00003770204,0.0000300942,0.00002445395],"domain_scores_gemma":[0.9993473,0.0004271573,0.00006189991,0.00005162785,0.00006410544,0.00004789984],"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":[0.0000333105,0.00003596054,0.003392007,0.00001429293,0.00002250911,0.00007103265,0.00003216652,0.9929044,0.0007649558,0.0005316595,0.00008749556,0.002110214],"study_design_scores_gemma":[0.00002309869,0.000009493289,0.002895622,0.000003621011,0.000007184989,0.00000756555,0.00001858547,0.996298,0.0002611815,0.0003512861,0.0001173187,0.000007082973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874585,0.0000950133,0.01079174,0.0001301995,0.000006863476,0.00002305463,0.0003564965,0.00009236447,0.001045722],"genre_scores_gemma":[0.9964576,0.00005476443,0.003096902,0.00001003439,0.000005054303,0.00002042071,0.0001523098,0.000008227291,0.0001946033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01994791,"threshold_uncertainty_score":0.03966361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1284756066631138,"score_gpt":0.295747116194822,"score_spread":0.1672715095317082,"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."}}