{"id":"W2016889110","doi":"10.1016/j.watres.2012.04.004","title":"Impact of reflection on the fluence rate distribution in a UV reactor with various inner walls as measured using a micro-fluorescent silica detector","year":2012,"lang":"en","type":"article","venue":"Water Research","topic":"TiO2 Photocatalysis and Solar Cells","field":"Energy","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Fluence; Materials science; Reflection (computer programming); Ultraviolet; Quartz; Optics; Diffuse reflection; Reflection coefficient; Aluminium; Distribution uniformity; Irradiation; Detector; Total internal reflection; Composite material; Analytical Chemistry (journal); Optoelectronics; Chemistry; Chromatography; Nuclear physics","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":[0.00118053,0.0005327726,0.0004942764,0.0002923345,0.0004144394,0.0009421953,0.0006289533,0.0007418625,0.001844682],"category_scores_gemma":[0.001620482,0.0006002134,0.0005264297,0.0002819357,0.000662484,0.0005697287,0.0003976008,0.0007970641,0.0005298157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007300402,"about_ca_system_score_gemma":0.0007793806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002459039,"about_ca_topic_score_gemma":0.002218299,"domain_scores_codex":[0.9992917,0.0001650237,0.00003910834,0.0001805298,0.0001814529,0.0001422241],"domain_scores_gemma":[0.9978108,0.001542473,0.0001920383,0.0001506791,0.0002036811,0.0001004327],"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":[0.001109693,0.00004531783,0.00159134,0.00004995136,0.00002559215,0.0000662015,0.0001498684,0.000727539,0.9929338,0.0001709258,0.0000732874,0.003056573],"study_design_scores_gemma":[0.0000106047,0.0001556906,0.001958811,0.00000405187,0.00001732744,0.00004370203,0.00003319989,0.001433313,0.9961436,0.00001180323,0.0001785211,0.000009431121],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896957,0.0005003759,0.0078685,0.00007297334,0.0000150038,0.00001213592,0.0001206393,0.0002037433,0.001511002],"genre_scores_gemma":[0.9935666,0.0003950749,0.004206435,0.00004585601,0.000007660537,0.000018027,0.0001711971,0.00011458,0.001474624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002459039,"threshold_uncertainty_score":0.006243289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08008426685585637,"score_gpt":0.3508767861463072,"score_spread":0.2707925192904508,"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."}}