{"id":"W1965886581","doi":"10.1016/j.fuel.2010.04.004","title":"Hg occurrence in coal and its removal before coal utilization","year":2010,"lang":"en","type":"article","venue":"Fuel","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National High-tech Research and Development Program; Project 211; Ministry of Science and Technology of the People's Republic of China; Ministry of Science and Technology, Taiwan; National Natural Science Foundation of China","keywords":"Anthracite; Coal; Pyrite; Flue gas; Mercury (programming language); Bituminous coal; Chemistry; Combustion; Coal combustion products; Pyrolysis; Environmental chemistry; Silicate; Extraction (chemistry); Mineralogy; Environmental science; Waste management; Chromatography; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001831284,0.0001352347,0.0002192072,0.000411517,0.0005419847,0.0003805615,0.0002133976,0.0003640953,0.001502444],"category_scores_gemma":[0.0003399935,0.0001252707,0.0002308798,0.0003823289,0.0002353267,0.0003023752,0.0001429956,0.0002340082,0.0002886637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004835597,"about_ca_system_score_gemma":0.0005678897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02478872,"about_ca_topic_score_gemma":0.03521349,"domain_scores_codex":[0.9998375,0.00002067995,0.00000780755,0.00003775138,0.00005257359,0.00004364892],"domain_scores_gemma":[0.9998412,0.00004413784,0.0000235648,0.00001133041,0.00005951405,0.0000201852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.009189017,0.001238714,0.3010505,0.0002676128,0.0001364252,0.0005797425,0.001126047,0.001551213,0.6539556,0.0006740158,0.0003738361,0.02985729],"study_design_scores_gemma":[0.00002215902,0.002834283,0.5376831,0.00001496504,0.00008974951,0.0002571365,0.001039084,0.001817385,0.4524261,0.0002115382,0.003578559,0.00002589168],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991714,0.00009989597,0.0001080389,0.000006974604,0.000004837861,0.000002958959,0.00005089886,0.000001918479,0.0005531369],"genre_scores_gemma":[0.9977741,0.00009072565,0.0001454876,0.000008218346,0.00000343842,0.000003580649,0.0001136111,0.000003207381,0.001857637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02478872,"threshold_uncertainty_score":0.04928893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03228592684597159,"score_gpt":0.2892853643017373,"score_spread":0.2569994374557657,"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."}}