{"id":"W2030067394","doi":"10.3390/w6061785","title":"Photocatalytic Degradation of Phenol and Phenol Derivatives Using a Nano-TiO2 Catalyst: Integrating Quantitative and Qualitative Factors Using Response Surface Methodology","year":2014,"lang":"en","type":"article","venue":"Water","topic":"TiO2 Photocatalysis and Solar Cells","field":"Energy","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Windsor","keywords":"Reaction rate constant; Phenol; Photocatalysis; Particle size; Degradation (telecommunications); Factorial experiment; Titanium dioxide; Particle (ecology); Catalysis; Chemistry; Chemical engineering; Nuclear chemistry; Materials science; Kinetics; Organic chemistry; Composite material; Physical chemistry","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":[0.0007464553,0.0006515541,0.0008077056,0.0003341511,0.0001331556,0.0005618385,0.0003917164,0.0006283075,0.0002595856],"category_scores_gemma":[0.0004821208,0.000304717,0.001077343,0.0005386791,0.0002977344,0.0002866977,0.000221175,0.0004334968,0.0001931336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006247039,"about_ca_system_score_gemma":0.0004718119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001683439,"about_ca_topic_score_gemma":0.002343388,"domain_scores_codex":[0.9992921,0.0001273461,0.00006436082,0.0001615338,0.0002862802,0.00006832487],"domain_scores_gemma":[0.999786,0.00006842687,0.00005567321,0.00001889213,0.00005919932,0.00001186194],"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":[0.0001003551,0.00005798255,0.0001812248,0.000116079,0.00001691981,0.00001730631,0.00001531169,0.0007155893,0.9962342,0.00002061338,0.000007905515,0.002516567],"study_design_scores_gemma":[0.00001319998,0.0006280286,0.001611952,0.00000411411,0.00003979215,0.00005006108,0.00001993219,0.00863723,0.9885693,0.00003975165,0.0003706697,0.00001598558],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474827,0.001946254,0.0495495,0.00006020957,0.00003041923,0.0001142342,0.0002132181,0.0001414226,0.0004621236],"genre_scores_gemma":[0.9476746,0.001926138,0.04836821,0.00005425055,0.0000132098,0.0002121564,0.0003321581,0.00003571198,0.00138356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001683439,"threshold_uncertainty_score":0.004532576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264480834770733,"score_gpt":0.3611073887581526,"score_spread":0.2346593052810792,"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."}}