{"id":"W2771118385","doi":"10.13031/aea.12252","title":"Enhancing Subsurface Drainage to Control Salinity in Dryland Agriculture","year":2017,"lang":"en","type":"article","venue":"Applied Engineering in Agriculture","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drainage; Hydrology (agriculture); Leaching (pedology); Environmental science; Soil water; Infiltration (HVAC); Soil salinity; Watertable control; Vadose zone; Irrigation; Groundwater; Precipitation; Salinity; Soil salinity control; Geology; Leaching model; Soil science; Agronomy; Geotechnical engineering; Geography; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001883508,0.0003990204,0.0004313545,0.0001169392,0.00009707048,0.0001702994,0.0004597284,0.000365755,0.000008869451],"category_scores_gemma":[0.00006955442,0.0003063165,0.00006207656,0.0003575456,0.00001275078,0.0001663305,0.0000503528,0.0007551856,0.0000609619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000159152,"about_ca_system_score_gemma":0.00000774453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007784857,"about_ca_topic_score_gemma":0.0008103033,"domain_scores_codex":[0.9985201,0.00000877596,0.0003371774,0.0003456674,0.0001909457,0.000597343],"domain_scores_gemma":[0.9992929,0.00006036416,0.00004273776,0.0004044706,0.00002965511,0.000169889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0000175995,0.00003299911,0.001401034,0.0001193155,0.00003682739,0.00005957276,0.0008848156,0.6916631,0.3028918,0.0007538419,0.001736048,0.0004030525],"study_design_scores_gemma":[0.005619301,0.00005955438,0.7831237,0.0006491876,0.00004934818,0.00002989392,0.0004848775,0.01692127,0.181053,0.0001533534,0.009435497,0.002421095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874983,0.0002430939,0.001576838,0.000142063,0.0005246265,0.0006017771,0.00001670186,0.0005285763,0.008868049],"genre_scores_gemma":[0.9987485,0.00002549544,0.0006120634,0.00005651779,0.0002519567,0.000126859,0.00002068819,0.00004078624,0.0001171225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7817227,"threshold_uncertainty_score":0.9999389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003689768894835397,"score_gpt":0.1793889782092009,"score_spread":0.1756992093143655,"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."}}