{"id":"W2890794343","doi":"10.3390/catal8100409","title":"Photocatalytic Treatment of An Actual Confectionery Wastewater Using Ag/TiO2/Fe2O3: Optimization of Photocatalytic Reactions Using Surface Response Methodology","year":2018,"lang":"en","type":"article","venue":"Catalysts","topic":"TiO2 Photocatalysis and Solar Cells","field":"Energy","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Photocatalysis; Response surface methodology; Wastewater; Titanium dioxide; Mineralization (soil science); Degradation (telecommunications); Materials science; Pollutant; Central composite design; Pulp and paper industry; Chemical engineering; Chemistry; Chromatography; Environmental engineering; Environmental science; Composite material; Organic chemistry; Catalysis; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009689314,0.0008301961,0.0009570341,0.0004807681,0.0003166512,0.0008637655,0.000601401,0.001017556,0.0002585262],"category_scores_gemma":[0.0005231595,0.0003070362,0.001127373,0.0006938967,0.0002682521,0.0004319353,0.0003959402,0.000614301,0.0001950681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005853706,"about_ca_system_score_gemma":0.0004066386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002158698,"about_ca_topic_score_gemma":0.003685786,"domain_scores_codex":[0.9992114,0.0001203599,0.0001256633,0.0001763453,0.0002578023,0.0001084166],"domain_scores_gemma":[0.9997583,0.00006081816,0.00006332537,0.00001862885,0.00008390745,0.00001502292],"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":[0.0001014753,0.0001222115,0.000263284,0.0001850443,0.00001468092,0.00005371011,0.00002502411,0.0009293463,0.9946955,0.0000227631,0.00002833857,0.0035587],"study_design_scores_gemma":[0.000009240594,0.0003584017,0.001929255,0.000006301814,0.00002747322,0.00005349665,0.00003199557,0.003210716,0.9939202,0.00001811821,0.0004207577,0.00001399469],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884039,0.001379658,0.008932533,0.00008775313,0.0000206284,0.0001004913,0.0001772223,0.00007165933,0.0008260534],"genre_scores_gemma":[0.9696541,0.001788976,0.0266349,0.0000763294,0.00001013788,0.0001603637,0.000337483,0.00003144567,0.001306219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002158698,"threshold_uncertainty_score":0.005124271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0929992125145878,"score_gpt":0.3335025089665016,"score_spread":0.2405032964519138,"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."}}