{"id":"W2062569065","doi":"10.1016/j.jhydrol.2013.11.036","title":"Water table fluctuations and soil biogeochemistry: An experimental approach using an automated soil column system","year":2013,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Water table; Water column; Soil water; Table (database); Soil science; Groundwater; Hydrology (agriculture); Environmental science; Geology; Geotechnical engineering; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002632077,0.0001083578,0.0002014271,0.00004255949,0.0002204648,0.00006664932,0.0001311162,0.00007110819,0.0002520795],"category_scores_gemma":[0.000004223936,0.00007838636,0.00002712914,0.00005649675,0.0001632423,0.0005947504,0.00009420016,0.00008350294,0.00002619753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164602,"about_ca_system_score_gemma":0.00000932513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006434869,"about_ca_topic_score_gemma":0.00002488946,"domain_scores_codex":[0.9990679,0.00009878299,0.0002855211,0.0001595505,0.0001657385,0.0002224949],"domain_scores_gemma":[0.9996064,0.000009644918,0.0001238532,0.0001116768,0.00003263798,0.000115815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001072584,0.0001855586,0.006091963,0.000006941685,0.00003112069,0.000008920811,0.001571316,0.002948327,0.9886485,0.000006090036,0.0002530003,0.0002375894],"study_design_scores_gemma":[0.001591006,0.0007192507,0.009883177,0.00001346153,0.00009900539,0.00218307,0.007166763,0.6713436,0.3057543,0.00006123722,0.0008069921,0.0003780989],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983116,0.00005444974,0.0009505323,0.00007187949,0.00009241761,0.00007959251,0.000001943494,0.00003484204,0.0004027481],"genre_scores_gemma":[0.9989582,0.000001546199,0.0007254212,0.00006914432,0.00005886124,0.000009611095,0.000007997854,0.000008862208,0.0001603924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6828942,"threshold_uncertainty_score":0.3196503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137802572616934,"score_gpt":0.2367407327678815,"score_spread":0.2229604755061881,"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."}}