{"id":"W3048838566","doi":"10.1016/j.cej.2020.126629","title":"Tannic acid/Fe3+ functionalized magnetic graphene oxide nanocomposite with high loading of silver nanoparticles as ultra-efficient catalyst and disinfectant for wastewater treatment","year":2020,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Nanomaterials for catalytic reactions","field":"Chemistry","cited_by":119,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Nanocomposite; Catalysis; Graphene; Tannic acid; Nanomaterials; Oxide; Aqueous solution; Materials science; Nanoparticle; Photocatalysis; Methylene blue; Chemical engineering; Chemistry; Nuclear chemistry; Nanotechnology; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00005102552,0.0002466249,0.0003561569,0.00005015261,0.0000669511,0.00006631915,0.0001030617,0.00006640569,0.0001466831],"category_scores_gemma":[0.0000569977,0.0001855108,0.000135799,0.000100058,0.00007103845,0.00008080521,0.0000214871,0.0001078387,0.00000338374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223249,"about_ca_system_score_gemma":0.00003745699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001114291,"about_ca_topic_score_gemma":1.389412e-7,"domain_scores_codex":[0.9988545,0.000004174653,0.000402376,0.0002464174,0.0001952955,0.0002972167],"domain_scores_gemma":[0.9993009,0.00008123456,0.0001296897,0.0001406075,0.00006373043,0.0002838182],"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":[0.0002704913,0.00009136667,0.00005057505,0.0001616894,0.0001689872,0.00001585201,0.0002024004,0.002426882,0.9964318,0.00007502467,0.00000902907,0.00009587121],"study_design_scores_gemma":[0.00206546,0.0001723928,0.00002904884,0.0001253442,0.0002419444,0.0004521478,0.00004248138,0.00162137,0.9945098,0.00001686598,0.0005102496,0.0002128507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985527,0.000395054,0.0005512373,0.0001467568,0.00008467864,0.0001180043,0.00006339302,0.00005923706,0.00002887189],"genre_scores_gemma":[0.9975176,0.00001802126,0.002151129,0.00001079817,0.0001477295,0.0000340204,0.00004602252,0.0000436671,0.00003095507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001921987,"threshold_uncertainty_score":0.7564911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007088283163133314,"score_gpt":0.1906983917838414,"score_spread":0.1836101086207081,"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."}}