{"id":"W4379376702","doi":"10.1021/acs.est.3c00888","title":"Electrical Energy Consumption of Multiscale UV-AOP Reactors for Micropollutant Removal in Drinking Water: Facilitated Prediction by Reaction Rate Constants Measured on a Mini-Fluidic Photoreaction System","year":2023,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Ultraviolet; Fluidics; Energy consumption; Chemistry; Reaction rate constant; Environmental science; Process engineering; Nuclear engineering; Materials science; Kinetics; Optoelectronics; Engineering; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004791954,0.0004652953,0.0004121994,0.0002539018,0.0001143335,0.0003105415,0.0004098231,0.0003769249,0.0003635714],"category_scores_gemma":[0.0006180606,0.0002395626,0.0004586413,0.0002021298,0.0001614463,0.0003992165,0.0002538871,0.000465412,0.0001200332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003086216,"about_ca_system_score_gemma":0.000257427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329924,"about_ca_topic_score_gemma":0.001685356,"domain_scores_codex":[0.9997929,0.00002237768,0.00001539842,0.00005698603,0.00009769342,0.00001471213],"domain_scores_gemma":[0.9998438,0.00006468047,0.00003823714,0.00001502768,0.00003232801,0.00000582333],"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":[0.00006147462,0.00004050089,0.001224766,0.0000968843,0.00001064091,0.00002585298,0.00002833438,0.007301075,0.9812485,0.00008647453,0.00003783302,0.00983759],"study_design_scores_gemma":[0.000009046009,0.0002290269,0.003718624,0.000007118288,0.00002619192,0.00003604262,0.00002895579,0.1378943,0.8575661,0.00007194078,0.0003889852,0.00002368112],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8842801,0.0006751738,0.1138175,0.00008359923,0.00002327665,0.00005371681,0.000225443,0.000328811,0.000512355],"genre_scores_gemma":[0.9583625,0.000700222,0.04017905,0.00002053409,0.000006182163,0.00008308445,0.0001167739,0.00002187678,0.0005097983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001329924,"threshold_uncertainty_score":0.0026443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010225796424027,"score_gpt":0.2225709603128698,"score_spread":0.2124687023486295,"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."}}