{"id":"W4404634449","doi":"10.1016/j.dwt.2024.100912","title":"Arsenic removal from water using marble powder waste: A comprehensive study on adsorption dynamics and machine learning predictions","year":2024,"lang":"en","type":"article","venue":"Desalination and Water Treatment","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Keyano College","funders":"Mehran University of Engineering and Technology; Higher Education Commision, Pakistan; Higher Education Commission, Pakistan","keywords":"Adsorption; Waste management; Arsenic; Environmental science; Materials science; Metallurgy; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007760696,0.0007033203,0.0006776177,0.000548244,0.0002537968,0.0005640104,0.0004088345,0.0006527002,0.0004256841],"category_scores_gemma":[0.001001588,0.0002515127,0.001039787,0.0006165801,0.000161885,0.0006819551,0.0002657484,0.000509956,0.0001397769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004385576,"about_ca_system_score_gemma":0.0004924703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00568643,"about_ca_topic_score_gemma":0.00433203,"domain_scores_codex":[0.9998323,0.00004052795,0.00001148937,0.00004722602,0.00005170717,0.00001682656],"domain_scores_gemma":[0.9997134,0.0001655075,0.00002475299,0.00002157422,0.00006484359,0.000009936901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002758481,0.0004752169,0.02197304,0.0006502631,0.0003198289,0.0003342971,0.0001635422,0.808571,0.04313307,0.00123165,0.0008843599,0.1219879],"study_design_scores_gemma":[0.000007470236,0.0001376255,0.005384456,0.00001414585,0.00004868508,0.00003797764,0.00002863052,0.9797642,0.01319471,0.0005290504,0.0008349131,0.00001807079],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.922761,0.002431008,0.07172426,0.0003280319,0.00002368716,0.00007163778,0.0006730726,0.0004196888,0.001567737],"genre_scores_gemma":[0.9737046,0.001565632,0.0225237,0.00003835079,0.00001764839,0.00007521355,0.001132412,0.00003278722,0.0009097097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00568643,"threshold_uncertainty_score":0.01130664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02301444435407807,"score_gpt":0.2506288947738216,"score_spread":0.2276144504197435,"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."}}