{"id":"W2967658610","doi":"10.13031/aim.201901842","title":"&amp;lt;i&amp;gt;Towards improving the DNDC model for simulating soil hydrology and tile drainage&amp;lt;/i&amp;gt;","year":2019,"lang":"en","type":"article","venue":"2019 Boston, Massachusetts July 7- July 10, 2019","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tile drainage; Environmental science; Drainage; Hydrology (agriculture); Biogeochemical cycle; Water quality; Soil water; Greenhouse gas; Irrigation; Soil science; Geology; Agronomy; Ecology; Geotechnical engineering","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":[0.0006064831,0.0005636025,0.0004136708,0.0002980334,0.000315717,0.0007930109,0.001107496,0.0006314953,0.00220986],"category_scores_gemma":[0.001266723,0.0002733237,0.0006077787,0.0004389815,0.0002831333,0.0006241912,0.0005975605,0.0007712226,0.000402508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335711,"about_ca_system_score_gemma":0.002061321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.155194,"about_ca_topic_score_gemma":0.08089516,"domain_scores_codex":[0.9998282,0.00004208532,0.00001111828,0.0000398639,0.00004545481,0.00003325542],"domain_scores_gemma":[0.9994805,0.0001378821,0.00003658816,0.00006329137,0.0002241593,0.00005763887],"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":[0.00003311843,0.00003740219,0.003022404,0.00002067713,0.00001122296,0.00002805278,0.00001164708,0.9870947,0.001656077,0.0006737703,0.000790495,0.006620394],"study_design_scores_gemma":[0.000007021955,0.000003919564,0.0001905674,0.000001906541,0.00000215039,0.000001326894,0.000002696239,0.9985683,0.0005603356,0.0001016245,0.0005578687,0.000002237477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5385788,0.0004141688,0.4262796,0.001226799,0.0002487557,0.0002336371,0.004110643,0.00511048,0.02379717],"genre_scores_gemma":[0.8872553,0.0001656612,0.1059088,0.0001279713,0.000026327,0.0001278252,0.002059751,0.0003079237,0.004020476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.155194,"threshold_uncertainty_score":0.3085814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751753596541362,"score_gpt":0.2422528178688277,"score_spread":0.2247352819034141,"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."}}