{"id":"W2557040035","doi":"10.1016/j.jconhyd.2016.11.001","title":"Delineating baseflow contribution areas for streams – A model and methods comparison","year":2016,"lang":"en","type":"article","venue":"Journal of Contaminant Hydrology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Baseflow; STREAMS; Environmental science; Hydrology (agriculture); Watershed; Discharge; Tracking (education); Plume; Particle (ecology); Computer science; Geology; Drainage basin; Meteorology; Streamflow; Geography; Geotechnical engineering","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":[0.00111574,0.0001224991,0.0003897689,0.00005162357,0.0001227784,0.00001300135,0.0001098573,0.00007577934,0.00003730198],"category_scores_gemma":[0.0002851727,0.00007337831,0.00008244149,0.00004388055,0.0001175459,0.000218214,0.00007244005,0.00007246286,0.000004450713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009789266,"about_ca_system_score_gemma":0.00001413544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001506326,"about_ca_topic_score_gemma":0.0001017455,"domain_scores_codex":[0.9988167,0.0001386787,0.0005157088,0.0001538739,0.0001366471,0.0002383784],"domain_scores_gemma":[0.9988669,0.0004782839,0.0003997754,0.00008201871,0.0000908133,0.00008223309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003529377,0.000099705,0.110436,0.000007093433,0.0000831195,0.000008935604,0.0004076656,0.000811713,0.08940802,0.0005931805,0.0006603166,0.7971314],"study_design_scores_gemma":[0.01345925,0.00374464,0.09177413,0.0001566581,0.0005605296,0.0005834216,0.0004139464,0.7603998,0.03258172,0.006190784,0.08941854,0.000716591],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4837551,0.0001111298,0.5151508,0.0007775939,0.0000800739,0.00008203636,0.000004974714,0.000003894908,0.00003441879],"genre_scores_gemma":[0.9821294,0.00004285426,0.0172395,0.0001669706,0.00005763663,0.00001340302,0.000001186452,0.000007420392,0.0003416286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7964147,"threshold_uncertainty_score":0.2992281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01688606646131906,"score_gpt":0.3131702886922387,"score_spread":0.2962842222309196,"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."}}