{"id":"W2757714830","doi":"10.1016/j.envpol.2017.09.051","title":"Arsenic removal by perilla leaf biochar in aqueous solutions and groundwater: An integrated spectroscopic and microscopic examination","year":2017,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":387,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Universität Bremen; University of Agriculture, Faisalabad; National Research Foundation of Korea; International Foundation for Science; Grand Challenges Canada; Higher Education Commission, Pakistan; Alexander von Humboldt-Stiftung","keywords":"Sorption; Chemistry; Arsenic; Arsenite; Arsenate; Aqueous solution; Biochar; Nuclear chemistry; Adsorption; XANES; Langmuir adsorption model; Sulfur; Environmental chemistry; Spectroscopy; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001213804,0.0001827457,0.0001030082,0.0002279529,0.0002049094,0.0001615142,0.0001708848,0.0002654109,0.0008604541],"category_scores_gemma":[0.00009443929,0.0001424621,0.0001515847,0.0001610337,0.0001715082,0.0001817816,0.0001267573,0.0002790869,0.0001703543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001419871,"about_ca_system_score_gemma":0.0001245027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001726847,"about_ca_topic_score_gemma":0.002309856,"domain_scores_codex":[0.99993,0.000007108387,0.000003727394,0.00001841203,0.00002609782,0.00001461082],"domain_scores_gemma":[0.9999496,0.00001178871,0.00001036855,0.000004343287,0.00001857388,0.000005294799],"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":[0.00002807916,0.000004370925,0.0001932285,0.000008941851,0.000001815483,0.00001291707,0.00001381519,0.00002123686,0.999151,0.00002481903,0.00001361755,0.0005261016],"study_design_scores_gemma":[0.000003533463,0.00008333276,0.006077129,0.000002225982,0.000008136763,0.00008423317,0.00008535443,0.0006168672,0.9923562,0.00004076502,0.0006378526,0.000004317464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935631,0.0003621314,0.00381729,0.00006404008,0.00001754387,0.000009304708,0.0002038118,0.00006311093,0.001899728],"genre_scores_gemma":[0.9956816,0.0002126486,0.002078277,0.00003761691,0.000005145916,0.000008937184,0.0001262972,0.00001095967,0.001838517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001726847,"threshold_uncertainty_score":0.003433645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00844728197081029,"score_gpt":0.2190460227534891,"score_spread":0.2105987407826788,"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."}}