{"id":"W4224024405","doi":"10.1021/acsomega.2c00074","title":"Modeling of Textile Dye Removal from Wastewater Using Innovative Oxidation Technologies (Fe(II)/Chlorine and H<sub>2</sub>O<sub>2</sub>/Periodate Processes): Artificial Neural Network-Particle Swarm Optimization Hybrid Model","year":2022,"lang":"en","type":"article","venue":"ACS Omega","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"King Saud University","keywords":"Particle swarm optimization; Periodate; Artificial neural network; Wastewater; Chlorine; Biological system; Computer science; Textile; Chemistry; Materials science; Engineering; Algorithm; Artificial intelligence; Environmental engineering; Organic chemistry; Composite material","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":[0.0002297416,0.0006102665,0.0004874278,0.0002234402,0.0002365105,0.0005678504,0.000477062,0.0010399,0.0005678586],"category_scores_gemma":[0.0003579129,0.0002770857,0.0006913669,0.0002706786,0.0002142194,0.0004382766,0.0002372918,0.0004079842,0.0001066317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007082225,"about_ca_system_score_gemma":0.0006270542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0140335,"about_ca_topic_score_gemma":0.01038497,"domain_scores_codex":[0.9999186,0.0000229016,0.000005886449,0.00001929218,0.00002133221,0.00001199895],"domain_scores_gemma":[0.9998742,0.00007216617,0.00001519665,0.000004438392,0.00002946869,0.000004547045],"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":[0.00002026255,0.00002463323,0.0006006432,0.00003124221,0.00001702597,0.00002251361,0.00001036289,0.9941631,0.002219174,0.0001423711,0.00004936557,0.002699359],"study_design_scores_gemma":[0.00000189257,0.00001413147,0.0002251767,0.000001185498,0.000003574873,0.000003449785,0.000003413888,0.9990652,0.0005684501,0.00005773912,0.00005383305,0.000002002608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.668446,0.0008353514,0.3198407,0.0004135703,0.00005763369,0.0001190519,0.0003106471,0.0003298022,0.009647341],"genre_scores_gemma":[0.9827033,0.0002633733,0.01413204,0.00002490427,0.000007286283,0.0001225563,0.0001100966,0.00001407451,0.002622299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0140335,"threshold_uncertainty_score":0.02790362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0277865539531914,"score_gpt":0.233842544332237,"score_spread":0.2060559903790456,"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."}}