{"id":"W4213433210","doi":"10.1016/j.jiec.2022.02.032","title":"β-Cyclodextrin functionalized magnetic nanoparticles for the removal of pharmaceutical residues in drinking water","year":2022,"lang":"en","type":"article","venue":"Journal of Industrial and Engineering Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Adsorption; Chemistry; Chemical engineering; Superparamagnetism; Freundlich equation; Miniemulsion; Emulsion; Magnetic nanoparticles; Emulsion polymerization; Nanoparticle; Polymerization; Chromatography; Nuclear chemistry; Organic chemistry; Magnetization; Polymer","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":[0.0001276572,0.000224303,0.0002167105,0.0001963732,0.0001464728,0.0002106369,0.0001618758,0.0003764821,0.0006619582],"category_scores_gemma":[0.0001287933,0.0001953526,0.0002039331,0.0000751896,0.0001509358,0.0001993209,0.0002014766,0.0002696359,0.0002291669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000214021,"about_ca_system_score_gemma":0.0001684833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008220859,"about_ca_topic_score_gemma":0.001454108,"domain_scores_codex":[0.9998899,0.00001353859,0.000008206615,0.00003064061,0.00003419779,0.00002357462],"domain_scores_gemma":[0.9999514,0.000009501116,0.000009068051,0.000003294093,0.00001804999,0.000008755092],"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":[0.00005296752,0.00001506209,0.00005245757,0.00003525262,0.000003673127,0.00001561888,0.000006654372,0.00008905413,0.9980927,0.00002697358,0.00004316643,0.001566352],"study_design_scores_gemma":[0.000003766477,0.00008702568,0.0005161533,0.000002393767,0.000008007282,0.0000274094,0.00001007953,0.001199314,0.9974378,0.000009790623,0.0006947039,0.000003529286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905696,0.001271779,0.005873969,0.0001036648,0.0000648177,0.00002049774,0.00006389786,0.00008025349,0.001951484],"genre_scores_gemma":[0.9933649,0.0005698001,0.002449961,0.00008168102,0.00001191901,0.00001298617,0.00005436031,0.00001078326,0.003443611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008220859,"threshold_uncertainty_score":0.002214491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04608365082321975,"score_gpt":0.274572061201066,"score_spread":0.2284884103778463,"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."}}