{"id":"W319457187","doi":"10.1016/j.ejrh.2015.04.004","title":"Assessing climate change impacts on water availability of snowmelt-dominated basins of the Upper Rio Grande basin","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrology Regional Studies","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Experimental Program to Stimulate Competitive Research; BC Cancer Agency; Bureau of Reclamation; New Mexico Space Grant Consortium; National Science Foundation","keywords":"Snowmelt; Environmental science; Climate change; Water year; Streamflow; Surface runoff; Hydrology (agriculture); Structural basin; Snow; Hydrograph; Climatology; Climate model; Drainage basin; Water resources; Physical geography; Geography; Meteorology; Geology; 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":[0.000219234,0.0002448866,0.0002291302,0.0002260825,0.0003509622,0.0005790808,0.0005698926,0.0003252429,0.001003624],"category_scores_gemma":[0.0007134634,0.0002049995,0.0003352063,0.0003837314,0.0002771586,0.0003086195,0.0003360725,0.0002068903,0.00006667652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500604,"about_ca_system_score_gemma":0.0009298305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2483502,"about_ca_topic_score_gemma":0.3522322,"domain_scores_codex":[0.9998782,0.00003841661,0.000004565617,0.00003205683,0.00001974773,0.00002699126],"domain_scores_gemma":[0.9997248,0.00009123028,0.00005637977,0.00002213847,0.00004975857,0.00005559393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001903452,0.0001839832,0.826024,0.00006288404,0.0003187038,0.0004123806,0.0003973359,0.1588978,0.004140954,0.0005900338,0.001901814,0.006879729],"study_design_scores_gemma":[0.00007287119,0.00009663869,0.8683009,0.00001945777,0.00008695097,0.00005907596,0.0007812025,0.1271195,0.0009585803,0.0002499913,0.002234342,0.00002047989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984323,0.00003484297,0.0001083819,0.00008447901,0.00000177201,0.000008436826,0.0004784501,0.00001756647,0.0008337023],"genre_scores_gemma":[0.9989061,0.00003928101,0.0001964466,0.00001340789,0.000002412492,0.00002014445,0.0005610707,0.000004461216,0.0002567656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2483502,"threshold_uncertainty_score":0.4938094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07515582795711909,"score_gpt":0.3081748772626185,"score_spread":0.2330190493054994,"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."}}