{"id":"W2106858894","doi":"10.5194/hess-17-565-2013","title":"An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources","year":2013,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":166,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Ouranos","funders":"Bayerisches Landesamt für Umwelt; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"Climate change; Environmental science; Climate model; Water resources; Hydrological modelling; Climatology; Streamflow; Hydrology (agriculture); Geography; Drainage basin; Geology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001982278,0.0001526273,0.0003586555,0.0002684724,0.0003940346,0.00004686978,0.000366278,0.00008905593,0.00004775228],"category_scores_gemma":[0.000009630265,0.00007154161,0.00005589433,0.0006553906,0.0004516688,0.0002912941,0.0001647857,0.0000822088,0.00007610852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000165579,"about_ca_system_score_gemma":0.000001152103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328507,"about_ca_topic_score_gemma":0.0002622964,"domain_scores_codex":[0.9980807,0.0004626543,0.0002386811,0.0004597736,0.0002425124,0.0005156357],"domain_scores_gemma":[0.999554,0.00009351544,0.00005475201,0.0002084202,0.000009226707,0.00008004068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001139688,0.0001357217,0.2701715,0.0000125789,0.00008308372,0.000003792528,0.01071171,0.7149366,0.000493517,0.002782521,0.0000286921,0.0005262736],"study_design_scores_gemma":[0.0001780547,0.001249837,0.5538051,0.000009772249,0.0001065378,0.000005697743,0.002161574,0.4415546,0.0001082622,0.0005681392,0.00007608035,0.0001764412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914823,0.00001803056,0.0002925942,0.001067552,0.00003198124,0.0005707729,0.000004768124,0.00001996774,0.006512082],"genre_scores_gemma":[0.9986892,0.00001216236,0.00007693878,0.001009392,0.00001474088,0.0001822778,0.000005362034,0.000002214353,0.000007763646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2836335,"threshold_uncertainty_score":0.3030636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04040033576007589,"score_gpt":0.2650784405879863,"score_spread":0.2246781048279104,"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."}}