{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006618492,0.000249122,0.0003129115,0.00006584891,0.0005740508,0.0001271811,0.0002622186,0.0001663572,0.0001391407],"category_scores_gemma":[0.000006890771,0.0001885947,0.00002015085,0.0002299778,0.000368968,0.0004363628,0.0003224148,0.0001703029,0.00004010941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004393148,"about_ca_system_score_gemma":0.00006562947,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6484435,"about_ca_topic_score_gemma":0.8190668,"domain_scores_codex":[0.9975911,0.0003482843,0.0002587721,0.0007840302,0.000238902,0.000778897],"domain_scores_gemma":[0.9993731,0.00005335413,0.00006315805,0.0002011783,0.000007213988,0.0003020414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005345443,0.00005799427,0.9784138,0.0000275583,0.00002935982,0.0001112683,0.007115732,0.00479971,0.007876911,0.0001617006,0.0005862492,0.0002851834],"study_design_scores_gemma":[0.0007340806,0.0004383182,0.991891,0.00003834794,0.00001765673,0.00003182092,0.001968254,0.004038583,0.0001112985,0.00006596131,0.0003951525,0.0002695657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934286,0.0001871835,0.000006406674,0.005216751,0.0002790357,0.000699795,0.000004942342,0.00003543161,0.0001417803],"genre_scores_gemma":[0.9977863,0.00003186812,0.0002921925,0.001520531,0.00006570106,0.00002470641,0.00000823249,0.000007741443,0.0002626784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1706234,"threshold_uncertainty_score":0.7690667,"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."}}