{"id":"W2232990698","doi":"10.1016/j.jhazmat.2016.01.007","title":"Mechanisms of mercury removal by biochars produced from different feedstocks determined using X-ray absorption spectroscopy","year":2016,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":152,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Government of Saskatchewan; Western Economic Diversification Canada; Basic Energy Sciences; Canadian Light Source; Natural Sciences and Engineering Research Council of Canada; University of Washington; Canadian Institutes of Health Research; National Research Council Canada; Canada Foundation for Innovation; University of Saskatchewan; Division of Earth Sciences; DuPont; U.S. Department of Energy","keywords":"Mercury (programming language); X-ray; X-ray absorption spectroscopy; Environmental chemistry; Spectroscopy; Absorption (acoustics); Chemistry; X-ray spectroscopy; Materials science; Absorption spectroscopy; Nuclear chemistry; Analytical Chemistry (journal); Optics; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004422006,0.0001889407,0.0005004535,0.00006263796,0.00007011633,0.00003295532,0.0001908397,0.00006706412,0.002198044],"category_scores_gemma":[0.00009100223,0.0001120279,0.00009767554,0.00005695175,0.0001044337,0.0002605644,0.00008415267,0.00004500688,0.00003713218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000178301,"about_ca_system_score_gemma":0.0000176055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009743094,"about_ca_topic_score_gemma":0.00000427822,"domain_scores_codex":[0.9982636,0.0001289009,0.0007402372,0.0001777241,0.0004578372,0.0002317029],"domain_scores_gemma":[0.9986869,0.00005232534,0.0009356927,0.0001844475,0.00003562061,0.0001050228],"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":[0.0001792011,0.00006009125,0.0003927592,0.00000709821,0.000051318,0.000008718682,0.000158657,0.000003216645,0.997312,0.000006741263,0.001049736,0.0007704505],"study_design_scores_gemma":[0.000699951,0.0002402446,0.005926557,0.0001184051,0.00007675875,0.000049103,0.00005545279,0.000002945731,0.9910077,0.001536289,0.0001442273,0.0001423618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926663,0.00006359533,0.005726737,0.000313768,0.0009058727,0.0001699827,0.0001066591,0.00001064824,0.00003641348],"genre_scores_gemma":[0.996315,0.00008947893,0.003273431,0.00005178439,0.0001381819,0.000002107139,0.000002776826,0.00001913309,0.0001081191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006304308,"threshold_uncertainty_score":0.9987141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597756915432986,"score_gpt":0.2521809364216683,"score_spread":0.2362033672673384,"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."}}