{"id":"W1984306435","doi":"10.2136/vzj2008.0158","title":"Modeling Impacts of Tile Drain Spacing and Depth on Nitrate‐Nitrogen Losses","year":2010,"lang":"en","type":"article","venue":"Vadose Zone Journal","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Tile drainage; Tile; Drainage; Environmental science; Hydrology (agriculture); Precipitation; Geology; Soil water; Soil science; Geotechnical engineering; Geography; Meteorology; Archaeology","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":[0.0003176617,0.0004388221,0.000239429,0.000203901,0.0001833354,0.0004022971,0.0004816435,0.0004600026,0.000594182],"category_scores_gemma":[0.0009058098,0.0003332845,0.0005006968,0.0001958582,0.0002724636,0.0003734987,0.0002904847,0.0002860801,0.00005119156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149002,"about_ca_system_score_gemma":0.0007315947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04331945,"about_ca_topic_score_gemma":0.02778538,"domain_scores_codex":[0.9999152,0.00001831881,0.000005211657,0.00002785762,0.00001017651,0.00002322464],"domain_scores_gemma":[0.999679,0.0001824249,0.00006346362,0.00001940246,0.00003834187,0.00001735419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004179175,0.00002351118,0.01771723,0.000006437376,0.00001614073,0.00003033726,0.00001284021,0.9789004,0.002047277,0.00009304528,0.00002921368,0.001081728],"study_design_scores_gemma":[0.00001511496,0.00004284695,0.009052043,0.000002650403,0.00001818009,0.00000880402,0.00001962911,0.9888027,0.001802642,0.0001252591,0.0001038975,0.000006135813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969833,0.00001994086,0.002257378,0.00001678027,0.000003063713,0.000007871949,0.0001221357,0.00002676236,0.0005627653],"genre_scores_gemma":[0.9986373,0.00002201271,0.001049043,0.000005415066,9.302632e-7,0.000007304823,0.00007422642,0.000004432352,0.0001992255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04331945,"threshold_uncertainty_score":0.08613455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008723295815200436,"score_gpt":0.2197489413981064,"score_spread":0.211025645582906,"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."}}