{"id":"W4415363362","doi":"10.5194/egusphere-2025-3851","title":"Technical Note: High Nash Sutcliffe Efficiencies conceal poor simulations of interannual variance in tropical, alpine, and polar catchments","year":2025,"lang":"","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Pacific Institute for Climate Solutions; University of Calgary; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Bundesministerium für Bildung und Forschung; Alexander von Humboldt-Stiftung","keywords":"Streamflow; Variance (accounting); Polar; Climate model; Climate change; Component (thermodynamics); Hydrological modelling; Series (stratigraphy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003354465,0.0003813493,0.0003468116,0.0005240042,0.0003615918,0.000987242,0.0006621437,0.0003939744,0.002733864],"category_scores_gemma":[0.01598381,0.0001809156,0.0003906653,0.0006938825,0.0006932156,0.001369281,0.001020684,0.0005560544,0.0003971432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008659587,"about_ca_system_score_gemma":0.001115738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01500241,"about_ca_topic_score_gemma":0.01470771,"domain_scores_codex":[0.9990762,0.0003949128,0.00006996166,0.0001245278,0.0002393069,0.00009514831],"domain_scores_gemma":[0.9928806,0.004510033,0.0005649975,0.0008265679,0.001015398,0.0002023539],"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":[0.0002013696,0.00007882906,0.1396971,0.0001047288,0.00011026,0.0004358742,0.0002134556,0.7896557,0.005969502,0.01278298,0.006481721,0.04426849],"study_design_scores_gemma":[0.00001849331,0.00005838235,0.02071115,0.00002253228,0.00002719587,0.0002130239,0.0001570723,0.9592854,0.01006027,0.006591235,0.002816071,0.00003918283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7420365,0.0006495467,0.2418707,0.00298703,0.0002353859,0.00007866167,0.001051335,0.001153094,0.009937695],"genre_scores_gemma":[0.9802703,0.0001296978,0.01794917,0.0001205606,0.00003016351,0.00002122665,0.0003930155,0.000122156,0.0009636689],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01500241,"threshold_uncertainty_score":0.02983016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009045715347180763,"score_gpt":0.266006740274296,"score_spread":0.2569610249271153,"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."}}