{"id":"W4310220101","doi":"10.1002/cjce.24785","title":"Modification of chitosan with cellulose and gelatin for the removal of Cu 2+ , Fe 2+ , and Pb 2+ from oily wastewater","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vaal University of Technology","keywords":"Adsorption; Nuclear chemistry; Fourier transform infrared spectroscopy; Conductivity; Wastewater; Scanning electron microscope; Chemistry; Chitosan; Cellulose; Solvent; Response surface methodology; Materials science; Chromatography; Chemical engineering; Waste management; Organic chemistry","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":[0.0001323777,0.0003889136,0.000202034,0.0001579571,0.0000892349,0.000210742,0.0001818105,0.0003570556,0.0006203171],"category_scores_gemma":[0.000222523,0.0001560916,0.000416672,0.0001378632,0.000151431,0.0002112836,0.0001632311,0.0002318442,0.0001463353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002072008,"about_ca_system_score_gemma":0.000226266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773161,"about_ca_topic_score_gemma":0.00298082,"domain_scores_codex":[0.9998516,0.00002277759,0.00001486626,0.0000240027,0.00005697492,0.00002979469],"domain_scores_gemma":[0.9998989,0.00001412858,0.00003771324,0.000007523897,0.0000279121,0.00001383004],"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":[0.0000348576,0.00001010053,0.0001211128,0.00004322159,0.00000655964,0.00005136946,0.000004961099,0.0001064198,0.998505,0.00001155149,0.00001168727,0.00109317],"study_design_scores_gemma":[0.000008065339,0.0001581762,0.002703068,0.000004953378,0.0000191587,0.0001513584,0.00001837298,0.001183628,0.9951007,0.000008833214,0.0006344286,0.000009157853],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936988,0.0009444436,0.004277092,0.0000736423,0.00002900677,0.00002664265,0.00005979123,0.00003396113,0.0008565854],"genre_scores_gemma":[0.9924827,0.0005367214,0.005246801,0.00007161609,0.000005395074,0.00001966781,0.00006581879,0.00001148442,0.001559712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001773161,"threshold_uncertainty_score":0.003525734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009481360776656112,"score_gpt":0.1812568018309142,"score_spread":0.1717754410542581,"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."}}