{"id":"W4408973501","doi":"10.1038/s41545-025-00454-6","title":"Development of an EOR-produced petroleum wastewater treatment system through integrated polyacrylonitrile membrane and ZrO2/sericin technologies: revelation of interactive mechanism based on synchrotron and XDLVO analyses","year":2025,"lang":"en","type":"article","venue":"npj Clean Water","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada); University of British Columbia; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Excellence Research Chairs, Government of Canada","keywords":"Polyacrylonitrile; Sericin; Chemical engineering; Membrane; Chemistry; Wastewater; Materials science; Waste management; Engineering; SILK; Polymer; Composite material; 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":[0.0002331679,0.0002688347,0.0004229905,0.0002450412,0.0001169819,0.00002434262,0.0001863349,0.0001586182,0.00007672407],"category_scores_gemma":[0.00003304865,0.0001710595,0.00003920728,0.0002471893,0.0002167692,0.0002673191,0.0001524646,0.0001159016,0.00001267558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003699546,"about_ca_system_score_gemma":0.00002144597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002012152,"about_ca_topic_score_gemma":0.00008104372,"domain_scores_codex":[0.9984206,0.00009907699,0.0005041485,0.0005197666,0.0002208682,0.0002355265],"domain_scores_gemma":[0.9992663,0.00005208944,0.0001755215,0.0004543946,0.00002594594,0.00002578467],"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":[0.0003475175,0.000141421,0.0005983319,0.000116953,0.00007268786,0.000003064555,0.001141438,0.001023232,0.9890452,0.0001913567,0.000007758103,0.007311056],"study_design_scores_gemma":[0.0007243428,0.0004695688,0.001082358,0.0001741824,0.00005343395,0.000002823376,0.006957904,0.009209122,0.9808392,0.0002105691,0.0001125541,0.0001639358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997425,0.00001289292,0.001016535,0.0002439702,0.00005062207,0.0004957398,0.00001113742,0.0002056378,0.0005384868],"genre_scores_gemma":[0.9895914,0.000009791801,0.0100697,0.00001671381,0.000002757805,0.00005370605,0.00003545543,0.00001461716,0.0002058557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009053169,"threshold_uncertainty_score":0.6975605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02095867155343907,"score_gpt":0.2787682641060885,"score_spread":0.2578095925526495,"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."}}