{"id":"W4254570924","doi":"10.5194/acpd-9-24051-2009","title":"Mercury emission and speciation of coal-fired power plants in China","year":2009,"lang":"en","type":"preprint","venue":"","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Mercury (programming language); Flue gas; Flue-gas desulfurization; Coal; Fly ash; Electrostatic precipitator; Environmental chemistry; Boiler (water heating); Bottom ash; Environmental science; Chemistry; Coal combustion products; Waste management; Environmental engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000172298,0.000339864,0.0001949917,0.0007995245,0.0004031196,0.0002035529,0.000259664,0.0002265499,0.0003989845],"category_scores_gemma":[0.000108046,0.0001390538,0.0002349073,0.0006874472,0.000157644,0.0002014385,0.0002139932,0.00009611928,0.00006546033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000882439,"about_ca_system_score_gemma":0.0004684444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04621166,"about_ca_topic_score_gemma":0.05681574,"domain_scores_codex":[0.9998674,0.000009547749,0.000008266418,0.00003487403,0.00005782551,0.00002210958],"domain_scores_gemma":[0.9999046,0.00001475239,0.00001937025,0.000006740005,0.0000384262,0.00001602885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002032969,0.0001089171,0.8816946,0.0001566895,0.0001459194,0.0007594504,0.0007699503,0.005212098,0.0883716,0.0001262302,0.0003187863,0.02213251],"study_design_scores_gemma":[0.000007068775,0.00004814116,0.9913421,0.000002192454,0.00001536495,0.00006741088,0.0001427508,0.002207187,0.00585671,0.00003205202,0.0002726587,0.000006286074],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995542,0.00003001134,0.00009752705,0.000006941688,5.45741e-7,0.000002557641,0.0001138008,0.000006134378,0.000188161],"genre_scores_gemma":[0.9991328,0.00003473261,0.0001316902,0.000009171429,0.000001383379,0.00000393529,0.0002499084,0.000001758919,0.0004345789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04621166,"threshold_uncertainty_score":0.09188533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373274757800106,"score_gpt":0.2606777187482368,"score_spread":0.2469449711702357,"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."}}