{"id":"W2073897467","doi":"10.5194/hess-17-2701-2013","title":"Potential surface temperature and shallow groundwater temperature response to climate change: an example from a small forested catchment in east-central New Brunswick (Canada)","year":2013,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Institut national de la recherche scientifique","keywords":"Environmental science; Climate change; Snow; Precipitation; Mean radiant temperature; Northern Hemisphere; Groundwater; Climatology; Surface water; Climate model; Hydrology (agriculture); Elevation (ballistics); Drainage basin; Range (aeronautics); Atmospheric sciences; Geology; Meteorology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002294956,0.0003621142,0.0003581776,0.0005886242,0.00158713,0.000977484,0.001091585,0.0005319339,0.001441451],"category_scores_gemma":[0.0005366745,0.0001978638,0.0005472669,0.002231958,0.0008781019,0.0002191677,0.0004581205,0.0004405836,0.0001019038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01955479,"about_ca_system_score_gemma":0.01085126,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.988227,"about_ca_topic_score_gemma":0.992146,"domain_scores_codex":[0.9998223,0.00002043487,0.000008896312,0.00003780621,0.00004147016,0.00006900493],"domain_scores_gemma":[0.9996507,0.00006117282,0.00002104565,0.00001657144,0.0001885924,0.00006175106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007717517,0.0006679095,0.7675231,0.0003033991,0.000274487,0.004548054,0.002180186,0.1826274,0.008953105,0.001957586,0.005659904,0.02453311],"study_design_scores_gemma":[0.0002517134,0.000105764,0.7714831,0.00005131764,0.000125001,0.0002136863,0.006649729,0.214355,0.002208991,0.0005314188,0.003915721,0.0001085813],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973952,0.00004506609,0.0001658922,0.0001132131,0.000003236022,0.00003721289,0.0009754217,0.0000205653,0.001244245],"genre_scores_gemma":[0.9982261,0.0000606526,0.0004407073,0.00003480864,0.000001363647,0.00001706329,0.0006030792,0.000005072649,0.000611302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01955479,"threshold_uncertainty_score":0.1418806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01616083687426363,"score_gpt":0.1993018455793937,"score_spread":0.1831410087051301,"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."}}