{"id":"W4322775929","doi":"10.1021/acssuschemeng.2c06794","title":"Development of Superpermeable Wood-Based Forward Osmosis Membranes","year":2023,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada's Oil Sands Innovation Alliance; China Scholarship Council","keywords":"Membrane; Glutaraldehyde; Vinyl alcohol; Chemical engineering; Materials science; Polyamide; Thin-film composite membrane; Layer (electronics); Interfacial polymerization; Reverse osmosis; Forward osmosis; Kraft paper; Polymer chemistry; Layer by layer; Composite material; Polymer; Chromatography; Chemistry; Monomer","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":[0.0002547874,0.0001928963,0.0001999991,0.00006352868,0.0001101728,0.00002419443,0.0003820336,0.0001230651,0.0006755046],"category_scores_gemma":[0.0002393393,0.0002069179,0.00004888078,0.0008745071,0.00006218514,0.000182338,0.0002557723,0.0001213271,0.00009460933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000267748,"about_ca_system_score_gemma":0.00005878293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002435606,"about_ca_topic_score_gemma":7.908601e-7,"domain_scores_codex":[0.9985435,0.000003708062,0.0002969652,0.000293882,0.0003073011,0.0005546534],"domain_scores_gemma":[0.9994283,0.00005314061,0.00005683043,0.0003623297,0.0000263593,0.00007309512],"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":[0.00000420625,0.00001909251,0.0003390801,0.000637823,0.00001339198,0.00001711705,0.0002411015,0.1909673,0.8069439,0.00004368552,0.0004114883,0.0003618544],"study_design_scores_gemma":[0.0001738071,0.000005367546,0.0002736028,0.00001911547,0.000006661342,0.000001692066,0.001214374,0.007086295,0.9401059,0.00003167068,0.05086889,0.000212692],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948931,0.0000426407,0.000693594,0.0001087378,0.00002373162,0.0001509949,0.000001793993,0.0006072343,0.003478204],"genre_scores_gemma":[0.9894548,0.0000102606,0.005060438,0.00001085819,0.00001144416,0.00009855227,0.00002770374,0.00003063505,0.005295285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.183881,"threshold_uncertainty_score":0.8437868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007738696638527055,"score_gpt":0.2037634516116544,"score_spread":0.1960247549731274,"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."}}