{"id":"W4410762169","doi":"10.1016/j.wroa.2025.100358","title":"Customizing surface grafting and interlayer functionalization for PFOA separation in polyamide membranes","year":2025,"lang":"en","type":"article","venue":"Water Research X","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Richard Lounsbery Foundation; U.S. Department of Agriculture; U.S. Environmental Protection Agency; National Science Foundation","keywords":"Surface modification; Polyamide; Grafting; Membrane; Materials science; Separation (statistics); Chemical engineering; Polymer chemistry; Chemistry; Composite material; Computer science; Polymer; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001281192,0.00007567147,0.00009205233,0.0001715493,0.0001978824,0.00008346546,0.0001335458,0.00007196493,0.0002213065],"category_scores_gemma":[0.000212734,0.00005944515,0.00001689689,0.0003257597,0.0001491062,0.000312529,0.0002173881,0.0001392268,0.0000919976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149855,"about_ca_system_score_gemma":0.00001030449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003515236,"about_ca_topic_score_gemma":0.0005141937,"domain_scores_codex":[0.9988763,0.0001130977,0.0001897201,0.000285817,0.0002354438,0.0002995972],"domain_scores_gemma":[0.9996659,0.0001221761,0.00001683219,0.000143941,0.00002707192,0.00002403943],"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":[0.0001810825,0.0000412394,0.05485464,0.0001222499,0.00001269623,0.000002076467,0.001227062,0.01302963,0.9191213,0.002309394,0.003724583,0.005374036],"study_design_scores_gemma":[0.0008487788,0.0000685281,0.009083215,0.00005836974,0.00000439785,0.000002093579,0.0006422026,0.04495957,0.9023896,0.01151224,0.03026138,0.0001696049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891431,0.00005698589,0.003148642,0.002052914,0.00006122585,0.0005414015,0.000001546122,0.00006759653,0.004926607],"genre_scores_gemma":[0.993605,0.00002876105,0.0007231159,0.00006395804,0.000009450129,0.00007770503,0.00001838735,0.000007126785,0.005466466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04577142,"threshold_uncertainty_score":0.2424103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05013595394930657,"score_gpt":0.3699803548634814,"score_spread":0.3198444009141748,"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."}}