{"id":"W4241294857","doi":"10.32920/ryerson.14663721.v1","title":"Modeling, simulation, and optimization of advanced oxidation technologies for treatment of polymeric wastewater","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Biodegradation; Effluent; Wastewater; Rendering (computer graphics); Aqueous solution; Sewage treatment; Sewage; Industrial wastewater treatment; Advanced oxidation process; Environmental science; Chemistry; Pulp and paper industry; Environmental chemistry; Computer science; Environmental engineering; Organic chemistry","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":[0.00005132347,0.0001085241,0.0002431965,0.00004968439,0.00002635886,0.00001272259,0.00006098302,0.00009927707,0.00002986996],"category_scores_gemma":[0.00001933537,0.0000862617,0.00007010602,0.00007441449,0.00004855881,0.00006653391,0.0001292699,0.00001600062,1.996239e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005300201,"about_ca_system_score_gemma":0.000005668725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000494685,"about_ca_topic_score_gemma":0.000004497167,"domain_scores_codex":[0.9992772,0.00001813186,0.0002755907,0.0002495498,0.0001062347,0.00007329295],"domain_scores_gemma":[0.9995908,0.00002258665,0.0001280587,0.0002220131,0.00002475525,0.00001178694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008798363,0.00005686525,0.0006242148,0.0000441268,0.00003069419,4.284819e-8,0.0003359363,0.9734858,0.01948437,0.00000189017,3.071599e-7,0.005926997],"study_design_scores_gemma":[0.00013384,0.00005148003,0.00002770951,0.0000215869,0.00005534342,5.189663e-8,0.0005883649,0.7414243,0.2575171,0.000108627,0.000003262835,0.00006830966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7436753,0.0001141527,0.255916,0.00006342374,0.00002828312,0.0001548807,0.000006116326,0.00002925018,0.00001259566],"genre_scores_gemma":[0.9262596,0.0001523527,0.07328834,6.273736e-7,0.000006252322,0.00002971926,0.00009179316,0.000006629393,0.0001646611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2380327,"threshold_uncertainty_score":0.351765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03032221606527867,"score_gpt":0.2875602233587677,"score_spread":0.257238007293489,"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."}}