{"id":"W1992867482","doi":"10.1016/j.gloenvcha.2013.05.004","title":"Nitrate in groundwater of China: Sources and driving forces","year":2013,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Groundwater and Isotope Geochemistry","field":"Earth and Planetary Sciences","cited_by":410,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Groundwater; Nitrate; Environmental science; Contamination; Hydrology (agriculture); Environmental chemistry; Population; Environmental engineering; Chemistry; Ecology; Geology; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005048095,0.0001045788,0.000114842,0.00001647398,0.00003765411,0.00003243355,0.00009238465,0.00004500362,0.00185549],"category_scores_gemma":[0.00000119356,0.00008376272,0.0000226933,0.00004175231,0.0001082348,0.0003254629,0.00002962369,0.00004675649,0.00009985061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007584457,"about_ca_system_score_gemma":0.000001462857,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009892645,"about_ca_topic_score_gemma":0.0008906645,"domain_scores_codex":[0.9993601,0.00001690505,0.0001257458,0.0001662895,0.0001126496,0.0002183348],"domain_scores_gemma":[0.9998136,0.000006804788,0.00003415591,0.00007671743,9.017305e-7,0.00006778398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003385388,0.00001481291,0.9903424,0.00001172031,0.000003733224,0.000002532997,0.0002686957,0.000005478575,0.0005700279,0.00000210337,0.000009940488,0.008765151],"study_design_scores_gemma":[0.0001687667,0.00005861132,0.9974784,0.00001217059,0.000003521219,0.0000141026,0.0004295463,0.0004021974,0.0006791984,0.0005196756,0.0001332044,0.0001006076],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960374,0.0006566058,0.000002972936,0.00005762683,0.00004138055,0.0001441535,0.00002833266,0.000007808629,0.003023776],"genre_scores_gemma":[0.9995887,0.00009438392,0.00006842022,0.0000661058,0.00003895822,0.000004465928,0.00005511295,0.000001643427,0.00008217232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009001981,"threshold_uncertainty_score":0.9990569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007686887962374497,"score_gpt":0.1691580857232126,"score_spread":0.1614711977608381,"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."}}