{"id":"W2083788947","doi":"10.1016/j.cherd.2008.06.001","title":"Optimization of phenol degradation in a combined photochemical–biological wastewater treatment system","year":2008,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Phenol; Degradation (telecommunications); Wastewater; Chemistry; Retention time; Bioreactor; Activated sludge; Process (computing); Hydraulic retention time; Photochemistry; Pulp and paper industry; Process engineering; Environmental science; Environmental engineering; Chromatography; Organic chemistry; Computer science","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":[0.00005891939,0.0001564513,0.0001709524,0.00003418198,0.0001243002,0.000003546827,0.0000477834,0.00007929136,0.0001688822],"category_scores_gemma":[0.000004335043,0.0001239454,0.00002628753,0.000101593,0.000163435,0.0002437811,0.00004064547,0.00005475698,0.00001759921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006044345,"about_ca_system_score_gemma":0.000003008949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001022109,"about_ca_topic_score_gemma":0.000004697758,"domain_scores_codex":[0.9990404,0.00004703127,0.0002946775,0.000315103,0.0001541497,0.0001486028],"domain_scores_gemma":[0.9997141,0.000009128392,0.0001209969,0.0001060542,0.000001661909,0.00004806442],"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":[0.001565347,0.001124503,0.08148421,0.00007505601,0.00002912368,0.00001111694,0.002122945,0.8185809,0.09019991,0.00001101022,7.232899e-7,0.004795216],"study_design_scores_gemma":[0.008972264,0.002455674,0.06234492,0.0001278215,0.00005378694,0.0002468723,0.002288303,0.392297,0.5299234,0.0002543082,0.0002077188,0.0008279563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699364,0.00002264012,0.02865295,0.0000371574,0.00001810739,0.00101126,0.00001042664,0.00003817341,0.0002728959],"genre_scores_gemma":[0.998309,0.0001671031,0.001074915,0.000005884804,0.000006489868,0.0002584704,0.00009398213,0.00001029507,0.00007388487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4397235,"threshold_uncertainty_score":0.5054345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487468991018142,"score_gpt":0.1972309810616156,"score_spread":0.1823562911514342,"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."}}