{"id":"W2582078439","doi":"","title":"Quantifying groundwater-surface water interactions using a stream energy balance model and dye tracing in a proglacial valley of the Cordillera Blanca, Peru","year":2015,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Groundwater; Surface water; Water balance; Hydrology (agriculture); Energy balance; Tracing; Environmental science; Geology; Geography; Environmental engineering; Computer science; Geotechnical engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002281877,0.0004635579,0.0003686452,0.0006046875,0.0006211924,0.0009763514,0.0007553307,0.0009700556,0.0005535642],"category_scores_gemma":[0.0008467698,0.0004048426,0.0005209878,0.0008420676,0.0003934769,0.0007587864,0.0006345559,0.0003440987,0.00009003399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00185349,"about_ca_system_score_gemma":0.001235445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2060603,"about_ca_topic_score_gemma":0.2596557,"domain_scores_codex":[0.9998927,0.0000283438,0.000006613321,0.00003523179,0.00001441908,0.00002276604],"domain_scores_gemma":[0.9998085,0.00009237275,0.00002250808,0.00001600204,0.0000373177,0.00002328963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004449244,0.0007444877,0.3958414,0.00009836107,0.0003402409,0.0007246662,0.0008216451,0.5541287,0.02363407,0.0009076262,0.0006000196,0.02171377],"study_design_scores_gemma":[0.0000832782,0.0001254576,0.1198123,0.000008674668,0.00007011892,0.00003823474,0.0004442396,0.8767692,0.002006012,0.0002139915,0.0003938756,0.00003461858],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998922,0.00001393486,0.0004742087,0.0000398949,8.880943e-7,0.000009345282,0.0001157728,0.00004213014,0.0003820085],"genre_scores_gemma":[0.9989179,0.00001964766,0.0007301126,0.00000535263,0.000001116909,0.00001088498,0.0001297015,0.000007431255,0.0001778942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2060603,"threshold_uncertainty_score":0.4097218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0407087534920114,"score_gpt":0.2600967647539199,"score_spread":0.2193880112619084,"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."}}