{"id":"W2771993775","doi":"10.3390/membranes7040068","title":"Study of Separation and Fouling of Reverse Osmosis Membranes during Model Hydrolysate Solution Filtration","year":2017,"lang":"en","type":"article","venue":"Membranes","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Collège Shawinigan; Centre National en Électrochimie et en Technologies Environnementales; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; BioFuelNet Canada","keywords":"Chemistry; Fouling; Nanofiltration; Furfural; Reverse osmosis; Chromatography; Pulp and paper industry; Membrane; Membrane fouling; Biorefinery; Forward osmosis; Sodium hydroxide; Filtration (mathematics); Membrane technology; Chemical engineering; Hemicellulose; Cellulose; Organic chemistry; Biochemistry; Raw material","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":[0.0004536013,0.0001220022,0.0002892448,0.00007626176,0.0005386699,0.00004560844,0.0001895289,0.00004061706,0.00001100788],"category_scores_gemma":[0.0002372559,0.0001092584,0.00003228359,0.00004729046,0.000182117,0.0006883221,0.0001559319,0.00005614058,0.000002678981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001988154,"about_ca_system_score_gemma":0.00002016497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002248491,"about_ca_topic_score_gemma":0.0001821058,"domain_scores_codex":[0.9987939,0.00007565822,0.0003249043,0.000267436,0.0003479108,0.0001901821],"domain_scores_gemma":[0.9989942,0.00006581874,0.0003578401,0.0004143901,0.0001304042,0.00003739059],"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":[0.0001083033,0.00009470269,0.0008953874,0.0004298355,0.00001675175,0.00000264737,0.002393159,0.01957525,0.9763268,0.00002093398,0.000002124882,0.0001340613],"study_design_scores_gemma":[0.0008143167,0.0001079824,0.002821633,0.00006198006,0.00003960355,0.000002406381,0.0008419617,0.02772125,0.9670953,0.0003808869,0.000002904541,0.0001097801],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985726,0.0002222737,0.0004516754,0.00007241218,0.0000744711,0.0003617788,0.000007245076,0.00002605531,0.0002114981],"genre_scores_gemma":[0.9987251,0.0003661732,0.0006943761,0.000001913875,0.00003143191,0.00002840623,0.000001895364,0.00001050539,0.0001402328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009231555,"threshold_uncertainty_score":0.445543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05107927640167898,"score_gpt":0.336574721151198,"score_spread":0.285495444749519,"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."}}