{"id":"W3035630731","doi":"10.1016/j.envpol.2020.115002","title":"Aqua regia digestion cannot completely extract Hg from biochar: A synchrotron-based study","year":2020,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada); University of Waterloo","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; China University of Geosciences, Wuhan; National Natural Science Foundation of China","keywords":"Aqua regia; Biochar; Chemistry; Mercury (programming language); Charcoal; Pyrolysis; Adsorption; Environmental chemistry; Digestion (alchemy); Detection limit; Nuclear chemistry; Chromatography; Metal","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":[0.0003534017,0.0002010837,0.0002782476,0.0001601159,0.0002892326,0.0002613046,0.000310926,0.0003401622,0.0007114689],"category_scores_gemma":[0.0001905385,0.0001672284,0.0003060353,0.0002027631,0.0003115759,0.0001871733,0.0002616327,0.0002873703,0.0001997518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001766707,"about_ca_system_score_gemma":0.0002315906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003184484,"about_ca_topic_score_gemma":0.003992045,"domain_scores_codex":[0.9998208,0.00002838498,0.0000123723,0.00004465781,0.00004925968,0.00004464026],"domain_scores_gemma":[0.9998761,0.00003687154,0.0000206467,0.0000262366,0.00003130219,0.000008751696],"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":[0.0002095724,0.00003292442,0.001316676,0.00002346696,0.00001500697,0.00003231015,0.00003866038,0.00008232522,0.9972808,0.00003584979,0.00003252874,0.0008998414],"study_design_scores_gemma":[0.00002370666,0.0003074813,0.01907489,0.000003638742,0.00004321821,0.0002506401,0.0001598713,0.001103215,0.9774753,0.00007506815,0.001475303,0.000007698246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981217,0.0001753161,0.001092769,0.00003244817,0.000004263847,0.000005141347,0.00008413109,0.0000108086,0.0004734157],"genre_scores_gemma":[0.997631,0.0001537158,0.001088028,0.00002428162,0.000003085108,0.000004461168,0.0001468593,0.000009232574,0.0009392404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003184484,"threshold_uncertainty_score":0.006331921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820445595378755,"score_gpt":0.2417663131780668,"score_spread":0.2135618572242793,"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."}}