{"id":"W4294982414","doi":"10.1039/d2ew00340f","title":"Ceramic membranes with <i>in situ</i> doped iron oxide nanoparticles for enhancement of antifouling characteristics and organic removal","year":2022,"lang":"en","type":"article","venue":"Environmental Science Water Research & Technology","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"Biofouling; Membrane; Nanoparticle; Ceramic; Materials science; Chemical engineering; Doping; Iron oxide; Nanotechnology; Chemistry; Composite material; Metallurgy; Engineering; Optoelectronics","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":[0.000171412,0.000298361,0.0002130547,0.0001495993,0.0002265354,0.0002326194,0.0003513411,0.0005612858,0.0005624648],"category_scores_gemma":[0.0001964599,0.0001690669,0.0003553019,0.0001391903,0.0001657999,0.0003130214,0.0001310689,0.0004061816,0.0001891194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002476908,"about_ca_system_score_gemma":0.0002570459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001590178,"about_ca_topic_score_gemma":0.003185394,"domain_scores_codex":[0.9998876,0.000008828019,0.000008606692,0.00002449226,0.00003330862,0.0000372721],"domain_scores_gemma":[0.9999329,0.00001258648,0.0000157589,0.000004836435,0.00002322071,0.00001064932],"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":[0.00002850683,0.000006591668,0.00002901825,0.00003032124,0.000002524469,0.00001875597,0.000008950179,0.00002340406,0.9992742,0.00004091426,0.00002608786,0.0005107651],"study_design_scores_gemma":[0.000002775915,0.00004601198,0.0003104691,0.000001288245,0.000007364368,0.00004034858,0.000009607878,0.000241878,0.9987657,0.000006520929,0.0005650565,0.000003001595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918801,0.0008772326,0.004828538,0.0001144537,0.00008203438,0.0000214479,0.0001019259,0.00009340207,0.002000886],"genre_scores_gemma":[0.993982,0.0004866811,0.003464086,0.00004145754,0.00001188939,0.00001066083,0.00008743212,0.00001454654,0.001901239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001590178,"threshold_uncertainty_score":0.003161848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809870318888203,"score_gpt":0.2713449264930392,"score_spread":0.2532462233041571,"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."}}