{"id":"W3106765428","doi":"10.1007/s10584-020-02892-2","title":"Performance evaluation of global hydrological models in six large Pan-Arctic watersheds","year":2020,"lang":"en","type":"article","venue":"Climatic Change","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Chinese Academy of Sciences; Bundesministerium für Bildung und Forschung","keywords":"Environmental science; Snow; Arctic; Permafrost; Climatology; Drainage basin; Discharge; Hydrology (agriculture); Climate change; Latitude; Precipitation; Physical geography; Meteorology; Geology; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002369646,0.0008015548,0.0006020014,0.0006840758,0.0003847802,0.0007213813,0.000442805,0.0004809952,0.0002988908],"category_scores_gemma":[0.00217889,0.0001962747,0.0007943427,0.0008556743,0.000328887,0.0006344401,0.000533775,0.0003241378,0.00006134564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057596,"about_ca_system_score_gemma":0.0008404992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03931147,"about_ca_topic_score_gemma":0.02017194,"domain_scores_codex":[0.9995742,0.0002065855,0.00003803106,0.00008070424,0.00005252116,0.00004785975],"domain_scores_gemma":[0.9991152,0.0004365658,0.00008844394,0.00008387019,0.0002046337,0.00007128201],"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":[0.0002286478,0.0002020479,0.08645332,0.00002955441,0.0002423937,0.00005611775,0.00006020745,0.8982375,0.001626231,0.0002061707,0.0002538578,0.01240393],"study_design_scores_gemma":[0.00002042374,0.0001253028,0.01611549,0.000003715681,0.00002638314,0.000007471074,0.00005265159,0.9821935,0.001229521,0.0001067381,0.000111213,0.000007490636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970449,0.00004167768,0.002122318,0.00003740894,0.000007454267,0.00001424314,0.0002244093,0.0001507083,0.0003569778],"genre_scores_gemma":[0.996803,0.00002985291,0.002588535,0.000008164881,0.000004154842,0.00001476267,0.0004646536,0.00001060639,0.00007628858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03931147,"threshold_uncertainty_score":0.07816529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1953430968527776,"score_gpt":0.3005276706798947,"score_spread":0.1051845738271171,"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."}}