{"id":"W3093711348","doi":"10.1039/d0ta07977d","title":"The preparation of waste biomass-derived N-doped carbons and their application in acid gas removal: focus on N functional groups","year":2020,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Industrial Gas Emission Control","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Public Health","funders":"Department of Science and Technology of Sichuan Province; Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Biomass (ecology); Resource recovery; Waste management; Biochar; Environmental science; Sustainable society; Municipal solid waste; Chemistry; Pulp and paper industry; Environmental chemistry; Materials science; Wastewater; Pyrolysis; Engineering; Sustainability; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002811707,0.0001108026,0.0002281052,0.00001865589,0.0000297874,0.00003298727,0.0001035941,0.0000976853,0.00002225296],"category_scores_gemma":[0.000146115,0.00007651301,0.00003993806,0.00007515413,0.00002511086,0.00006036713,0.00001753209,0.0001223206,8.279243e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004654158,"about_ca_system_score_gemma":0.00003358966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002548043,"about_ca_topic_score_gemma":5.08827e-7,"domain_scores_codex":[0.9991343,0.00003900941,0.0005058302,0.00008440006,0.0001358729,0.0001006068],"domain_scores_gemma":[0.9994419,0.00007435116,0.0002586741,0.0001024822,0.00005896673,0.00006363294],"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":[0.0006010174,0.0000107064,0.000006004489,0.00004767032,0.00003175762,0.00000336266,0.0001411753,0.0009682447,0.9972829,0.00001004895,0.0002900385,0.0006070351],"study_design_scores_gemma":[0.0008730622,0.00004734976,0.00005365561,0.00005033857,0.00001176791,0.00004068147,0.0001333507,0.001608749,0.9964812,0.0001345345,0.0005008895,0.00006443041],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978917,0.000150078,0.0004299413,0.0009681297,0.0001426929,0.0001220908,0.00001177446,0.00001545405,0.0002681028],"genre_scores_gemma":[0.9993355,0.00004295935,0.00004461635,0.00001229508,0.0005304681,0.000008660141,0.000003669761,0.0000137966,0.000007984931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001443814,"threshold_uncertainty_score":0.312011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545374598881937,"score_gpt":0.2186136378704425,"score_spread":0.2031598918816231,"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."}}