{"id":"W4224288484","doi":"10.1002/cjce.24421","title":"Efficient recovery of phenol from phenolic wastewater by emulsion liquid membrane","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emulsion; Phenol; Kerosene; Chromatography; Chemistry; Extraction (chemistry); Tributyl phosphate; Breakage; Wastewater; Materials science; Organic chemistry; Waste management; Composite material","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":[0.0001199759,0.00009673589,0.0001614246,0.0001047632,0.00005673432,0.00001906137,0.0002229,0.00004849467,0.0004595658],"category_scores_gemma":[0.00004267193,0.00008283369,0.00006823348,0.00015664,0.00001805932,0.0000466126,0.00001227507,0.0004677668,0.000003119532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000186236,"about_ca_system_score_gemma":0.00006795731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002749077,"about_ca_topic_score_gemma":0.00002268191,"domain_scores_codex":[0.9992527,0.00001148603,0.0003145837,0.00005671053,0.0001940176,0.0001705221],"domain_scores_gemma":[0.9995434,0.0000643732,0.00006634506,0.0001016585,0.00004306672,0.0001812159],"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":[0.00001155588,0.000003658914,6.124914e-7,0.00001151625,0.00002306878,0.000002909677,0.0002649735,0.4960366,0.5026067,0.00001126794,0.0009572425,0.00006992858],"study_design_scores_gemma":[0.0002340725,0.00004034551,0.000002011729,0.00002836845,0.00002106233,0.0000445536,0.00006544679,0.06825086,0.91831,0.00002232903,0.01286143,0.0001195318],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972739,0.001176136,0.0004547531,0.0002236079,0.0004580535,0.00004067075,0.00004066933,0.00002056577,0.0003116695],"genre_scores_gemma":[0.9996744,0.000005927383,0.0001022115,0.00004635941,0.000092521,0.000003375082,0.00000767907,0.00002316717,0.00004431472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4277857,"threshold_uncertainty_score":0.5031923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005884811994728869,"score_gpt":0.1770406600287456,"score_spread":0.1711558480340167,"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."}}