{"id":"W4239731806","doi":"10.1139/l00-091","title":"Advanced technologies in water and wastewater treatment","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wastewater; Filtration (mathematics); Sewage treatment; Water treatment; Environmental science; Waste management; Emerging technologies; Industrial wastewater treatment; Process engineering; Environmental engineering; Engineering; Biochemical engineering; Nanotechnology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007196837,0.00008128894,0.0001117886,0.0002031063,0.00002304803,0.00001763843,0.0001100698,0.00005047127,0.0002703717],"category_scores_gemma":[0.00003268033,0.00005713098,0.00001779518,0.0001028228,0.00004905161,0.0001809776,0.00001555238,0.00008701061,0.0000123795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002392048,"about_ca_system_score_gemma":0.00001382913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003667083,"about_ca_topic_score_gemma":0.08458943,"domain_scores_codex":[0.9994858,0.000003679736,0.0001548352,0.00007477368,0.00005507026,0.0002258353],"domain_scores_gemma":[0.9997935,0.000008666206,0.00002295043,0.00009016965,0.000003429914,0.00008122849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000026041,0.00002968127,0.1413923,0.00002395018,0.0000417758,0.001815452,0.002588028,0.5260504,0.2671637,0.0001983854,0.0005241366,0.06014614],"study_design_scores_gemma":[0.002860056,0.0009101953,0.0396468,0.0002322647,0.00003042947,0.002000383,0.002579618,0.009023984,0.5459646,0.002041633,0.393741,0.0009690762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976688,0.0002780153,0.00009065199,0.0007459264,0.00006931829,0.00005152236,3.87734e-7,0.00002787324,0.001067511],"genre_scores_gemma":[0.9993449,0.0001208809,0.0003898178,0.00000668927,0.000005701477,0.000003009838,3.138368e-7,0.000006812816,0.0001219076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5170265,"threshold_uncertainty_score":0.9321144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006752089843983754,"score_gpt":0.1834861873831555,"score_spread":0.1767340975391717,"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."}}