{"id":"W1995881101","doi":"10.13031/2013.32109","title":"A Comparison of DRAINMOD and SWAT for Surface Runoff and Subsurface Drainage Flow Prediction at the Field Scale for a Cold Climate","year":2010,"lang":"en","type":"article","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Hydrology (agriculture); Drainage; Surface runoff; Tile drainage; Soil and Water Assessment Tool; SWAT model; Subsurface flow; Outflow; Runoff curve number; Streamflow; Soil water; Drainage basin; Soil science; Geology; Groundwater; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007174218,0.0006241186,0.0003011606,0.0005294351,0.0002870541,0.0005891597,0.0005863123,0.0002921275,0.001183392],"category_scores_gemma":[0.001315122,0.000276824,0.0003196293,0.0005167454,0.0002092966,0.0005288536,0.0003097461,0.000256648,0.0003143795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002059022,"about_ca_system_score_gemma":0.001784862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2341952,"about_ca_topic_score_gemma":0.3911249,"domain_scores_codex":[0.9998199,0.00003038954,0.000008713911,0.00005116387,0.00006681873,0.00002296997],"domain_scores_gemma":[0.9993829,0.0001505,0.00006565022,0.0000832923,0.000262176,0.00005543338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001000158,0.0004299854,0.5516794,0.0001325324,0.0002256823,0.0001607641,0.0003356374,0.2760729,0.03162934,0.0009040648,0.004610831,0.1328187],"study_design_scores_gemma":[0.0001174949,0.0002499303,0.2250884,0.0000226451,0.00005794499,0.00006048815,0.0002286329,0.7573586,0.0109594,0.0002703749,0.005530592,0.00005541872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816253,0.00008302525,0.011779,0.00008580424,0.0000130721,0.00005326416,0.002549513,0.001207816,0.002603364],"genre_scores_gemma":[0.9812505,0.00007431333,0.01388642,0.00003224201,0.000003469041,0.00005179788,0.003239714,0.00009599851,0.001365501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2341952,"threshold_uncertainty_score":0.465664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008844838018226097,"score_gpt":0.2604146630445965,"score_spread":0.2515698250263704,"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."}}