{"id":"W4387735687","doi":"10.1021/acsestwater.3c00215","title":"Machine Learning for Heavy Metal Removal from Water: Recent Advances and Challenges","year":2023,"lang":"en","type":"article","venue":"ACS ES&T Water","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Suncor Energy (Canada)","funders":"Southeast University; National Research Foundation of Korea; Rural Development Administration; Korea University","keywords":"Computer science; Implementation; Biochar; Data science; Engineering; Waste management; Software 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":[0.003206187,0.0008280704,0.001476889,0.00102893,0.0003708243,0.002119757,0.001348695,0.001505081,0.002055294],"category_scores_gemma":[0.005145217,0.0004917814,0.001248327,0.001700757,0.0008577862,0.002954016,0.00120016,0.002805902,0.0009783794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008124804,"about_ca_system_score_gemma":0.001392956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672943,"about_ca_topic_score_gemma":0.001357478,"domain_scores_codex":[0.9990735,0.0002709794,0.00009572617,0.0002234637,0.0002822899,0.00005395819],"domain_scores_gemma":[0.9961542,0.002809514,0.0001753454,0.000123627,0.0006592957,0.00007791362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001125933,0.0001403725,0.001723733,0.01376123,0.0002618338,0.0001833712,0.0002857284,0.01930028,0.003851274,0.0256215,0.01219409,0.9225639],"study_design_scores_gemma":[0.00007539934,0.0009713679,0.004521382,0.006217368,0.0006074472,0.0008883257,0.0006330754,0.1246263,0.0118038,0.09893973,0.7504569,0.0002588481],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004460512,0.9460172,0.04100863,0.004377892,0.0005501616,0.00003985363,0.00009920964,0.0001492586,0.003297294],"genre_scores_gemma":[0.03070248,0.9433643,0.02179391,0.001105252,0.001355551,0.00008262617,0.000244821,0.0000462309,0.001304919],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003206187,"threshold_uncertainty_score":0.01695615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0582817784144826,"score_gpt":0.2717285397397013,"score_spread":0.2134467613252188,"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."}}