{"id":"W2464509330","doi":"10.1007/s10333-016-0538-y","title":"Converting rice paddy to dry land farming in the Tai Lake Basin, China: toward an understanding of environmental and economic impacts","year":2016,"lang":"en","type":"article","venue":"Paddy and Water Environment","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Chinese Academy of Sciences; China Association for Science and Technology","keywords":"Agriculture; Environmental science; Surface runoff; Environmental impact of agriculture; Agricultural land; Land use; Nutrient pollution; Paddy field; Agricultural pollution; Nutrient management; Pollution; Water resource management; Agricultural economics; Geography; Economics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004641354,0.0002058158,0.0001977729,0.00004557413,0.0001280188,0.00003237657,0.000167119,0.00006198031,0.0002134534],"category_scores_gemma":[0.000002800544,0.0001118972,0.00003143042,0.00002033336,0.0002550228,0.0002935973,0.0002894334,0.00007887982,0.00007621783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002474195,"about_ca_system_score_gemma":0.000001893026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002439412,"about_ca_topic_score_gemma":0.00007538515,"domain_scores_codex":[0.9986314,0.0000948174,0.0002845942,0.0004089197,0.0001877298,0.0003925592],"domain_scores_gemma":[0.999512,0.00005745826,0.00006130733,0.0002221787,2.446845e-7,0.000146856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004723814,0.000081161,0.9799484,0.0000109518,0.00001061966,0.000008451391,0.006075863,0.0001265286,0.01112789,0.00002130918,0.000007650113,0.002533921],"study_design_scores_gemma":[0.001116929,0.0002754763,0.9877983,0.00003268519,0.00002726018,0.00001722125,0.001380255,0.0004845272,0.004717118,0.002620127,0.001203991,0.0003260946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979057,0.00002904671,0.0005307782,0.0009927026,0.000045851,0.0002596939,0.00005295997,0.000008819433,0.0001744484],"genre_scores_gemma":[0.9992559,0.0002662731,0.0001399399,0.0002290363,0.00002647868,0.00001609873,0.00001101194,0.00001680014,0.00003844717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007849897,"threshold_uncertainty_score":0.4563036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225860931009058,"score_gpt":0.1939907998990029,"score_spread":0.1817321905889123,"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."}}