{"id":"W2906710521","doi":"10.1029/2018gl080260","title":"Observed Spatiotemporal Changes in the Mechanisms of Extreme Water Available for Runoff in the Western United States","year":2019,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Strategic Environmental Research and Development Program; Natural Resources Conservation Service; Battelle; Commission for Environmental Cooperation; U.S. Department of Energy","keywords":"Snowmelt; Snowpack; Environmental science; Hydrometeorology; Snow; Surface runoff; Climatology; Climate change; Water year; Hydrology (agriculture); Water resources; Atmospheric sciences; Precipitation; Meteorology; Geography; Geology; Oceanography; 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":[0.000306927,0.0001070223,0.0001528492,0.0006255392,0.0002071804,0.0003995159,0.0001974307,0.0001461601,0.0004444738],"category_scores_gemma":[0.0006943134,0.00009848547,0.0001227386,0.0009338857,0.000205203,0.0002739101,0.000343223,0.0001627404,0.00005976544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003639223,"about_ca_system_score_gemma":0.0002168941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04074688,"about_ca_topic_score_gemma":0.07466154,"domain_scores_codex":[0.9998974,0.00002317688,0.00001052307,0.00003163423,0.0000206949,0.00001661349],"domain_scores_gemma":[0.9994848,0.00008143843,0.0002389722,0.00004572815,0.0001040573,0.00004500736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003334017,0.00002149354,0.9944003,0.000008606075,0.00005687771,0.00003347982,0.0001577159,0.0003709673,0.001116461,0.00006236973,0.0003376306,0.003400874],"study_design_scores_gemma":[8.484081e-7,0.000006513447,0.9992251,0.000002108595,0.000005532975,0.00001261205,0.00008909253,0.0002801327,0.0001122548,0.00001221096,0.00025219,0.000001342701],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988697,0.00008411557,0.0001165874,0.00003710605,0.000002484255,0.000002290461,0.0005743144,0.000007787647,0.0003055573],"genre_scores_gemma":[0.999236,0.00005697243,0.0001009347,0.00001215848,0.000003236894,0.000004150324,0.0005269139,0.000001398749,0.00005826084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04074688,"threshold_uncertainty_score":0.0810194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1332146497411722,"score_gpt":0.2853608050322389,"score_spread":0.1521461552910667,"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."}}