{"id":"W3006401624","doi":"10.1016/j.biortech.2020.122978","title":"As(III) and As(V) removal mechanisms by Fe-modified biochar characterized using synchrotron-based X-ray absorption spectroscopy and confocal micro-X-ray fluorescence imaging","year":2020,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; Major Science and Technology Program for Water Pollution Control and Treatment; National Natural Science Foundation of China","keywords":"Pyrolysis; Biochar; XANES; Absorption (acoustics); Chemistry; Analytical Chemistry (journal); Fluorescence; Synchrotron; Spectroscopy; X-ray fluorescence; Fluorescence spectroscopy; X-ray; Nuclear chemistry; Materials science; Chromatography; Optics","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":[0.0001268371,0.0002164425,0.0002383723,0.0001740861,0.0002216665,0.0003360573,0.0003139506,0.0003381004,0.00045983],"category_scores_gemma":[0.0001481431,0.0001662091,0.0002754792,0.0001681122,0.0001670473,0.0002404727,0.0001168668,0.00028681,0.0001608277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004051767,"about_ca_system_score_gemma":0.000223206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004117849,"about_ca_topic_score_gemma":0.005558993,"domain_scores_codex":[0.999889,0.000008237409,0.000007869484,0.00002318969,0.00003792404,0.00003376935],"domain_scores_gemma":[0.9999514,0.000008058511,0.00000859524,0.000005149946,0.00002232359,0.000004578657],"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":[0.00005829688,0.000009324939,0.000172361,0.00001659928,0.000003877642,0.00002028125,0.00001513153,0.0002753971,0.9984724,0.00006539166,0.00001997781,0.0008708751],"study_design_scores_gemma":[0.000002567738,0.00003686017,0.001094008,0.000001580629,0.000005782824,0.00002213891,0.00002513291,0.002229773,0.9960929,0.0000309899,0.0004537402,0.000004537969],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961128,0.0003129313,0.002565584,0.00002752825,0.00001549042,0.00001092764,0.0001760052,0.00004951854,0.0007292909],"genre_scores_gemma":[0.9956979,0.0002476816,0.00267008,0.0000125759,0.000002656164,0.000009238019,0.0001388327,0.00001090267,0.001210213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004117849,"threshold_uncertainty_score":0.008187771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006952750192114464,"score_gpt":0.2202649093834451,"score_spread":0.2133121591913307,"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."}}