{"id":"W2609657555","doi":"10.1002/2016wr020209","title":"Simulating seasonal variations of tile drainage discharge in an agricultural catchment","year":2017,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Tile drainage; Drainage basin; Hydrology (agriculture); Drainage; Environmental science; Discharge; Agriculture; Water resource management; Geography; Geology; Archaeology; Soil science; Geotechnical engineering; Soil water; Cartography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001070362,0.00008541312,0.0001228761,0.00005963174,0.0008856364,0.00008519937,0.0005374717,0.00004392026,0.0006180641],"category_scores_gemma":[0.00005263893,0.00005217161,0.00002867345,0.00006578957,0.0004292342,0.0003275196,0.001161293,0.0001918303,0.0002050051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006602921,"about_ca_system_score_gemma":0.000001402087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001491287,"about_ca_topic_score_gemma":0.0007092236,"domain_scores_codex":[0.9984679,0.0001980965,0.000159249,0.0002732404,0.0004337494,0.0004678298],"domain_scores_gemma":[0.9994786,0.00004332796,0.00004025642,0.0003594301,0.0000141704,0.00006420793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005140814,0.0002607109,0.9426299,0.00002812884,0.00002714416,0.00001958183,0.03058498,0.005811993,0.01885036,0.0003250295,0.0003415458,0.001069245],"study_design_scores_gemma":[0.0003945006,0.0001106761,0.9855714,0.00001565139,0.000004802922,4.618673e-7,0.0007902209,0.004429895,0.003065297,0.001299153,0.004200781,0.0001171129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9687822,0.000005192401,0.000009227836,0.0015399,0.00002269185,0.0002260258,0.000004160905,0.000009913118,0.02940065],"genre_scores_gemma":[0.9966573,0.000002212318,0.00008593118,0.00001670642,0.00003584247,0.00003681392,0.00001169111,0.000005735027,0.003147809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04294158,"threshold_uncertainty_score":0.6811689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04304440831509636,"score_gpt":0.3326402961175091,"score_spread":0.2895958878024127,"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."}}