{"id":"W2964132501","doi":"10.1016/j.jes.2019.07.008","title":"Robust magnetic laccase-mimicking nanozyme for oxidizing o-phenylenediamine and removing phenolic pollutants","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Sciences","topic":"Advanced Nanomaterials in Catalysis","field":"Materials Science","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Overseas Expertise Introduction Project for Discipline Innovation; Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China; National Science Foundation","keywords":"Laccase; Chemistry; Oxidizing agent; Catalysis; Environmental remediation; Guanosine; Nuclear chemistry; Contamination; Inorganic chemistry; Organic chemistry; Enzyme; Biochemistry","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":[0.0001455927,0.0003537104,0.0002388751,0.0001481722,0.000122192,0.0003415078,0.0004045123,0.0004840829,0.0006553758],"category_scores_gemma":[0.0001774897,0.0001452386,0.00029799,0.000109806,0.0001685892,0.0002388474,0.0002166872,0.0003708983,0.0003230892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000254943,"about_ca_system_score_gemma":0.0001468533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000332859,"about_ca_topic_score_gemma":0.0006898534,"domain_scores_codex":[0.9998498,0.00001459618,0.00001002231,0.00004412639,0.00004755741,0.00003392111],"domain_scores_gemma":[0.9999229,0.000008329809,0.00001796672,0.000008003383,0.00002003965,0.00002279932],"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":[0.00003571336,0.00001436686,0.00003498008,0.00002312658,0.000004107289,0.0000242312,0.00000502522,0.00003400401,0.9984363,0.00004514459,0.0000449936,0.001297942],"study_design_scores_gemma":[0.000005919269,0.00006611851,0.0002618117,0.000001058197,0.000007274517,0.00006181542,0.000005678078,0.0006237768,0.9979897,0.00001247652,0.0009614863,0.000002919551],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9665806,0.002106088,0.02738755,0.0003331317,0.0001639927,0.00005426598,0.0002180001,0.0005231866,0.002633155],"genre_scores_gemma":[0.9880555,0.0003716683,0.008490859,0.00008613436,0.0000196962,0.00002433956,0.0001826066,0.00002283696,0.002746435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006553758,"threshold_uncertainty_score":0.002192497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967287676543602,"score_gpt":0.2329521962950489,"score_spread":0.2132793195296129,"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."}}