{"id":"W2086403441","doi":"10.1021/ef900294s","title":"Measurement of Vapor Phase Mercury Emissions at Coal-Fired Power Plants Using Regular and Speciating Sorbent Traps with In-Stack and Out-of-Stack Sampling Methods<sup>†</sup>","year":2009,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stack (abstract data type); Sorbent; Coal; Mercury (programming language); Environmental science; Sampling (signal processing); Vapor phase; Waste management; Chemistry; Nuclear engineering; Process engineering; Environmental chemistry; Computer science; Engineering; Adsorption; Physics","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":[0.0009043429,0.000347779,0.0002496401,0.0003889842,0.0005382092,0.0002898371,0.0007152171,0.000418758,0.0002560391],"category_scores_gemma":[0.001084314,0.0002647697,0.0002518804,0.0004027241,0.0003112642,0.0002851417,0.0003029956,0.0001866734,0.0001185515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005981349,"about_ca_system_score_gemma":0.0004499035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009361407,"about_ca_topic_score_gemma":0.03432374,"domain_scores_codex":[0.9986039,0.0002853672,0.00005873882,0.0002894918,0.0006972604,0.00006534666],"domain_scores_gemma":[0.999212,0.0001795966,0.0001510116,0.00006757511,0.0003490159,0.00004078674],"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":[0.0007071694,0.0003027912,0.1642189,0.000206995,0.000112757,0.0001409179,0.0005486736,0.001355054,0.7897322,0.00004349382,0.0001486584,0.0424823],"study_design_scores_gemma":[0.00005055652,0.003263482,0.2820441,0.00001399349,0.0001299767,0.0004408431,0.0003918665,0.007777266,0.7043931,0.00003564152,0.001420393,0.0000386573],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952376,0.00009262028,0.004024898,0.00001409709,0.000004579734,0.00007154849,0.0001285459,0.00004476933,0.0003813609],"genre_scores_gemma":[0.9775836,0.0001205458,0.02134478,0.00002887844,0.000006343504,0.00006835197,0.0002745691,0.00001484825,0.0005581338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009361407,"threshold_uncertainty_score":0.01861387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06669150910898801,"score_gpt":0.3309397071942802,"score_spread":0.2642481980852922,"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."}}