{"id":"W2914764507","doi":"10.1002/cjce.23471","title":"Activated carbon impregnation with ag and cu composed nanoparticles for <i>escherichia coli</i> contaminated water treatment","year":2019,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microporous material; Scanning electron microscope; Crystallite; Copper; Metal; Nuclear chemistry; Materials science; Transmission electron microscopy; Specific surface area; Carbon fibers; Activated carbon; Mesoporous material; Analytical Chemistry (journal); Chemistry; Nanotechnology; Adsorption; Metallurgy; Chromatography; Organic chemistry; Composite number; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00006287097,0.0003155527,0.0001768905,0.0002292298,0.0001202799,0.000229753,0.0002359306,0.000341161,0.0005289027],"category_scores_gemma":[0.0001196191,0.0001291886,0.0002874345,0.0001717753,0.0001466667,0.0001475548,0.0001423179,0.0002141224,0.0002034665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001954336,"about_ca_system_score_gemma":0.000173434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229592,"about_ca_topic_score_gemma":0.002408612,"domain_scores_codex":[0.9998901,0.00000980547,0.000007320232,0.00002784093,0.0000399541,0.00002507587],"domain_scores_gemma":[0.9999486,0.000007920822,0.00001552309,0.00000538345,0.00001479467,0.000007793279],"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":[0.00002518672,0.000007469304,0.00007408884,0.0000364175,0.000003257867,0.00002826485,0.000005960856,0.00008328563,0.9983209,0.00002348048,0.00001850561,0.001373188],"study_design_scores_gemma":[0.000001850825,0.00007095941,0.0007471371,0.000002676775,0.000008855055,0.00005283021,0.000006399382,0.0005429927,0.9979398,0.000009241441,0.0006139465,0.000003327074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857894,0.001271921,0.01028785,0.0000703553,0.00005201059,0.00003764835,0.0001297204,0.0002084706,0.002152486],"genre_scores_gemma":[0.9894077,0.0005324776,0.007960567,0.00003338125,0.000007793032,0.00001882273,0.0001109682,0.00003222132,0.001896166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001229592,"threshold_uncertainty_score":0.002444863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007064254621047005,"score_gpt":0.1830909446977107,"score_spread":0.1760266900766637,"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."}}