{"id":"W2123079653","doi":"10.5539/jas.v6n5p120","title":"Using DSSAT-CENTURY Model to Simulate Soil Organic Carbon Dynamics Under a Low-Input Maize Cropping System","year":2014,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"DSSAT; Soil carbon; Environmental science; Tillage; Soil fertility; Cropping system; Conservation agriculture; Soil water; Agronomy; Soil management; Soil organic matter; Agroforestry; Agriculture; Crop yield; Soil science; Crop; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005050583,0.0009971714,0.0008079504,0.000556399,0.0006569944,0.001076775,0.001274892,0.001785193,0.002596469],"category_scores_gemma":[0.0008955653,0.0004502338,0.001132311,0.0008749482,0.0004492773,0.000599789,0.000492444,0.001135114,0.0003020698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002016847,"about_ca_system_score_gemma":0.001522276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1111631,"about_ca_topic_score_gemma":0.05508199,"domain_scores_codex":[0.9998438,0.00004008147,0.00001166409,0.00003719164,0.00002521485,0.00004190515],"domain_scores_gemma":[0.9994097,0.0002672439,0.00004916196,0.0000317221,0.0001677326,0.00007436705],"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":[0.00007898866,0.00005198132,0.003090074,0.00003040101,0.00003149236,0.00005996175,0.00002468852,0.9945076,0.0005399993,0.0003117443,0.0003444861,0.0009285525],"study_design_scores_gemma":[0.00002978132,0.00002256527,0.001011589,0.000003707037,0.00001264719,0.000005289706,0.00002505554,0.9981744,0.0002698254,0.0001211827,0.0003153604,0.00000855756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802969,0.0002121176,0.007291154,0.0003182152,0.0000751694,0.0000896503,0.004343207,0.0006026967,0.00677094],"genre_scores_gemma":[0.9913402,0.0001130604,0.004682031,0.00004557371,0.00000970708,0.00009293082,0.002166559,0.0000397988,0.001510233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1111631,"threshold_uncertainty_score":0.2210322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929643295966613,"score_gpt":0.2283709607866085,"score_spread":0.2090745278269424,"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."}}