{"id":"W4412776279","doi":"10.1016/j.desal.2025.119261","title":"Comprehensive technologies for heavy metal remediation: Adsorption, membrane processes, photocatalysis, and AI-driven design","year":2025,"lang":"en","type":"article","venue":"Desalination","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"King Fahd University of Petroleum and Minerals","keywords":"Environmental remediation; Photocatalysis; Adsorption; Heavy metals; Waste management; Metal; Environmental science; Chemical engineering; Engineering; Materials science; Environmental chemistry; Chemistry; Metallurgy; Contamination; Catalysis; 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":[0.0002181107,0.0001535127,0.0001875617,0.0001834298,0.0001721366,0.00005474363,0.0002179056,0.0001712495,0.00003652787],"category_scores_gemma":[0.0006121011,0.0001471562,0.00003163225,0.0008079426,0.0002477736,0.0004127788,0.0001126525,0.00009888531,0.00003121937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001138527,"about_ca_system_score_gemma":0.00003449381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001634737,"about_ca_topic_score_gemma":0.00003940569,"domain_scores_codex":[0.9989122,0.00004324729,0.0002745587,0.0003899846,0.0002066677,0.0001733848],"domain_scores_gemma":[0.9992704,0.0002173991,0.0001297238,0.0002489786,0.0001141882,0.00001925194],"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":[0.000487787,0.0004327666,0.006065364,0.001102214,0.0002581567,0.000003874398,0.0009411733,0.03243315,0.8211018,0.01998373,0.01980768,0.09738228],"study_design_scores_gemma":[0.0006943909,0.0001200382,0.001576953,0.00002822352,0.0000736564,0.000003944016,0.0004164672,0.02908147,0.9347544,0.01486297,0.01815325,0.0002342042],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1716516,0.001189886,0.8080218,0.0111696,0.0002729168,0.004458488,0.00003416443,0.002048797,0.001152786],"genre_scores_gemma":[0.9762108,0.0003127881,0.02216202,0.0002228114,0.00001024613,0.0005927577,0.0001039686,0.00001099703,0.000373564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8045593,"threshold_uncertainty_score":0.6000854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134568190175153,"score_gpt":0.2763713989453111,"score_spread":0.2550257170435596,"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."}}