{"id":"W2386987386","doi":"","title":"Characters and evaluation of nitrogen pollution in the water and surface sediment from six urban lakes in Beijing","year":2011,"lang":"en","type":"article","venue":"Huadong Shifan Daxue xuebao. Ziran kexue ban","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sediment; Pollution; Environmental science; Eutrophication; Surface water; Water quality; Hydrology (agriculture); Total organic carbon; Beijing; Water pollution; Nitrogen; Nutrient pollution; Environmental chemistry; Environmental engineering; Ecology; Nutrient; Geology; Geography; Chemistry; China","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":[],"consensus_categories":[],"category_scores_codex":[0.002222055,0.0001778926,0.0002041993,0.00007138261,0.00009534994,0.00004282308,0.0001872613,0.00009033053,0.0003039042],"category_scores_gemma":[0.00001785027,0.0001185247,0.00003277076,0.0001538594,0.0002025767,0.0003882454,0.0001060341,0.0001683974,0.00002115232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001455385,"about_ca_system_score_gemma":0.00001468052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004826801,"about_ca_topic_score_gemma":0.003370231,"domain_scores_codex":[0.9977819,0.0006645969,0.0003982699,0.0003546743,0.0005025262,0.0002980867],"domain_scores_gemma":[0.9995005,0.00004776409,0.0001050119,0.0002693525,0.000009893158,0.00006752073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009303194,0.0002214292,0.9220316,0.0000218915,0.00002202213,0.00000651306,0.04601483,0.0002829964,0.02895462,0.0002513097,0.00008131122,0.002018475],"study_design_scores_gemma":[0.001085372,0.00006374472,0.9816827,0.00005183445,0.00004526457,0.000002422298,0.001375415,0.001134795,0.01316975,0.0008839887,0.0003113872,0.0001933515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997677,0.00008632426,0.00001640593,0.0009217554,0.00007598171,0.0005003205,0.00002897767,0.00001268596,0.0006805404],"genre_scores_gemma":[0.9993553,0.00001473419,0.0002186265,0.0002784244,0.00002561045,0.00002167814,0.00004345139,0.0000115673,0.00003067909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0596511,"threshold_uncertainty_score":0.7296712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05090765532208804,"score_gpt":0.2602241039397648,"score_spread":0.2093164486176768,"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."}}