{"id":"W2322672973","doi":"10.1002/ceat.201500622","title":"Fabrication of Chitosan Membranes with High Flux by Magnetic Alignment of In Situ Generated Fe<sub>3</sub>O<sub>4</sub>","year":2016,"lang":"en","type":"article","venue":"Chemical Engineering & Technology","topic":"Membrane Separation and Gas Transport","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science Fund for Distinguished Young Scholars; Project 211; National Natural Science Foundation of China","keywords":"Pervaporation; Membrane; Crystallinity; Magnetic field; Chitosan; Materials science; Fabrication; In situ; Dehydration; Chemical engineering; Glutaraldehyde; Ion; Analytical Chemistry (journal); Characterization (materials science); Magnetic flux; Flux (metallurgy); Chemistry; Nanotechnology; Chromatography; Composite material; Organic chemistry; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001378578,0.0005406201,0.0002118878,0.0002421044,0.0002317774,0.0002382135,0.0002644264,0.0005670768,0.0005907931],"category_scores_gemma":[0.0001596672,0.0002158018,0.0003113571,0.0002389198,0.0001874466,0.0003965159,0.0002343136,0.0003376194,0.0002495059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005375943,"about_ca_system_score_gemma":0.0003012013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0019595,"about_ca_topic_score_gemma":0.003227181,"domain_scores_codex":[0.9999197,0.000006929738,0.000006615846,0.0000165395,0.00003435919,0.00001584712],"domain_scores_gemma":[0.9998847,0.00001314027,0.00003879031,0.000009065026,0.00003787121,0.00001637847],"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":[0.00001144109,0.000003710382,0.00002506951,0.0000214163,0.000003104401,0.00001971485,0.000005304602,0.00005230664,0.9991991,0.00005187188,0.000031133,0.0005759102],"study_design_scores_gemma":[0.000008573822,0.0000299507,0.0005164194,0.000001989385,0.000009189889,0.00005292165,0.000008483702,0.0006392458,0.9976727,0.00001507715,0.001039877,0.000005512233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589152,0.001005421,0.03516825,0.0003178637,0.0001079982,0.0001028028,0.0003422416,0.0003493291,0.003690958],"genre_scores_gemma":[0.9523224,0.000781008,0.04249334,0.0001111515,0.00002448445,0.00006345678,0.0002051435,0.00005674652,0.003942259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0019595,"threshold_uncertainty_score":0.003900528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003299777480160708,"score_gpt":0.1660022924359328,"score_spread":0.1627025149557721,"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."}}