{"id":"W2906263038","doi":"10.2172/950967","title":"Evaluation of Sorbent Injection for Mercury Control","year":2008,"lang":"en","type":"report","venue":"","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sorbent; Power station; Mercury (programming language); Engineering; Waste management; Coal; Elemental mercury; Environmental science; Process engineering; Systems engineering; Computer science; Electrical engineering; Chemistry","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":[0.0008057868,0.0003699697,0.000342671,0.0003557225,0.0002960342,0.0005342726,0.0004787541,0.0003008237,0.001882795],"category_scores_gemma":[0.000594105,0.0001000497,0.0002332748,0.0002468675,0.0002300013,0.0003003216,0.0002190768,0.000259096,0.0004259313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006512285,"about_ca_system_score_gemma":0.0007409383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003168329,"about_ca_topic_score_gemma":0.008186741,"domain_scores_codex":[0.9989071,0.0001450075,0.00002313155,0.00009050986,0.000780216,0.00005412922],"domain_scores_gemma":[0.9996353,0.00006491067,0.00003486274,0.00002052471,0.0002209832,0.00002331128],"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":[0.0006271188,0.0006639929,0.003457761,0.0005560104,0.0000343269,0.00009962426,0.0001086629,0.003403463,0.8860961,0.0003713062,0.0009563413,0.1036252],"study_design_scores_gemma":[0.00004587965,0.004245844,0.004472437,0.000009874989,0.00003405086,0.00009487754,0.00005154351,0.003251371,0.9813579,0.0000518249,0.006373077,0.00001128606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508047,0.002162006,0.02429068,0.0001988522,0.00008881136,0.0006744567,0.0008051435,0.0006392669,0.02033609],"genre_scores_gemma":[0.952704,0.001991211,0.02495457,0.0001158488,0.00002142095,0.0001604496,0.001061389,0.00009459499,0.01889656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003168329,"threshold_uncertainty_score":0.006299734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09091268242377187,"score_gpt":0.3549110090754001,"score_spread":0.2639983266516283,"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."}}