{"id":"W2626273230","doi":"10.1016/j.watres.2017.06.045","title":"The influence of iron oxide nanoparticles upon the adsorption of organic matter on magnetic powdered activated carbon","year":2017,"lang":"en","type":"article","venue":"Water Research","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Adsorption; Maghemite; Mesoporous material; Iron oxide; Chemistry; Chemical engineering; Nanoparticle; Activated carbon; Mass fraction; Specific surface area; Carbon fibers; Iron oxide nanoparticles; Magnetic nanoparticles; Diffusion; Powdered activated carbon treatment; Inorganic chemistry; Materials science; Composite number; Organic chemistry; Catalysis; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000156756,0.0002214772,0.0001837555,0.000176791,0.0002423125,0.0002779782,0.0002190163,0.0003498366,0.0008267648],"category_scores_gemma":[0.0003417823,0.0001306924,0.0001905061,0.00008002709,0.0002568629,0.00021597,0.0001060938,0.0002932375,0.0001722224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002846669,"about_ca_system_score_gemma":0.0001630537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001762999,"about_ca_topic_score_gemma":0.002573481,"domain_scores_codex":[0.9998407,0.00001957256,0.00000921094,0.00002635785,0.00005843169,0.0000457416],"domain_scores_gemma":[0.9998392,0.00006950402,0.00002170402,0.00001030348,0.00004201744,0.00001716405],"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":[0.0002801106,0.0000334156,0.0001751811,0.00006074657,0.000009331588,0.00005675973,0.00002583773,0.0001432866,0.997465,0.00006328661,0.00006345813,0.001623635],"study_design_scores_gemma":[0.000006380549,0.0001441984,0.001593675,0.000002157091,0.000008101169,0.00002472257,0.00001868204,0.001068099,0.9967866,0.00001420985,0.0003286575,0.000004565564],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984218,0.0002946965,0.0003109061,0.00003852321,0.00002204103,0.000005266565,0.00002785771,0.00001634032,0.0008626202],"genre_scores_gemma":[0.9988518,0.0001118093,0.0002614653,0.00001905963,0.000009467454,0.000003005193,0.00003424441,0.000005468525,0.0007037245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001762999,"threshold_uncertainty_score":0.003505468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0262694027268817,"score_gpt":0.2858931205371498,"score_spread":0.2596237178102681,"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."}}