{"id":"W1643537079","doi":"10.1029/2006wr005603","title":"Application of a fully‐integrated surface‐subsurface flow model at the watershed‐scale: A case study","year":2008,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Baseflow; Subsurface flow; Hydrology (agriculture); Surface runoff; Hydrograph; Watershed; Environmental science; Streamflow; Vflo; Time of concentration; Hydrological modelling; Base flow; Geology; Drainage basin; Groundwater; Climatology; Geotechnical engineering; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002835204,0.0005107666,0.0003648355,0.0001934903,0.0005581311,0.0009235026,0.001074102,0.0007531511,0.001092322],"category_scores_gemma":[0.0008744276,0.0002898575,0.0003889909,0.0004500429,0.0005672838,0.000353093,0.0003977792,0.0003721644,0.0000745745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003116832,"about_ca_system_score_gemma":0.003117112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4425919,"about_ca_topic_score_gemma":0.3222754,"domain_scores_codex":[0.9998871,0.00002699714,0.000006547254,0.00002719705,0.00002513671,0.00002696186],"domain_scores_gemma":[0.9997774,0.00008888235,0.00002137752,0.00002687053,0.00006412465,0.00002140909],"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":[0.00003098361,0.00004020371,0.006163778,0.0000115665,0.000009663189,0.0001092822,0.00004993193,0.9894032,0.0009987343,0.0003492709,0.00008579498,0.002747587],"study_design_scores_gemma":[0.0000151264,0.00002996001,0.002475097,0.000001867881,0.000005786363,0.00001103595,0.00005339676,0.9966189,0.0004780584,0.0001333539,0.000171523,0.000005838023],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881639,0.00002258156,0.009293198,0.00007842473,0.00000468874,0.00005478711,0.0002867353,0.0001580118,0.001937491],"genre_scores_gemma":[0.9954639,0.00002276957,0.003904852,0.000006411674,0.00000112596,0.00002448796,0.0001110893,0.000007638787,0.0004577413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4425919,"threshold_uncertainty_score":0.8800315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04387474059734659,"score_gpt":0.2965171679684626,"score_spread":0.252642427371116,"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."}}