{"id":"W4410797706","doi":"10.1021/acsestwater.5c00238","title":"The Critical Role of Artificial Intelligence in Optimizing Electrochemical Processes for Water and Wastewater Remediation: A State-of-the-Art Review","year":2025,"lang":"en","type":"review","venue":"ACS ES&T Water","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"","keywords":"Wastewater; Environmental remediation; Environmental science; Process engineering; Biochemical engineering; Waste management; Computer science; Environmental engineering; Engineering; Ecology; Contamination; Biology","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":[0.0003047056,0.0002762904,0.0009453429,0.00004166419,0.00009835781,0.00003540027,0.0004947158,0.0001648429,0.00002006172],"category_scores_gemma":[0.0003394487,0.0001197997,0.0002796435,0.0002278105,0.0001795866,0.00004301705,0.0002021196,0.0003384632,0.000004624089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000391717,"about_ca_system_score_gemma":0.0001091168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001452921,"about_ca_topic_score_gemma":0.000007746367,"domain_scores_codex":[0.9978796,0.00003891112,0.001092864,0.0003920882,0.0001810749,0.0004154819],"domain_scores_gemma":[0.99861,0.0005902291,0.000141405,0.0004218363,0.0001940828,0.00004244002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000522116,0.0002800518,0.000004472787,0.2690306,0.0003260245,6.247822e-7,0.0002821655,0.000001937399,0.2595491,0.001150502,0.0004544409,0.4688679],"study_design_scores_gemma":[0.00002051109,0.000008462401,6.308167e-9,0.01076931,0.0004787496,0.000003283587,0.000007020692,0.00001783582,0.7486742,0.005444655,0.2344266,0.0001493592],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002884091,0.9978362,0.0001870036,0.001065482,0.00001342559,0.0004841464,0.0000226504,0.00001065604,0.00009197427],"genre_scores_gemma":[0.001238707,0.9969961,0.0002754642,0.00004342489,0.00006484738,0.00078954,0.000235986,0.00002351689,0.0003323932],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4891251,"threshold_uncertainty_score":0.4885292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692319043456457,"score_gpt":0.305635556278009,"score_spread":0.2887123658434445,"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."}}