{"id":"W4401209221","doi":"10.3390/chemengineering8040078","title":"Arsenic in Water: Understanding the Chemistry, Health Implications, Quantification and Removal Strategies","year":2024,"lang":"en","type":"article","venue":"ChemEngineering","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arsenic; Metalloid; Groundwater; Arsenic contamination of groundwater; Environmental science; Arsenate; Contamination; Human health; Arsenic toxicity; Environmental health; Environmental chemistry; Water resource management; Environmental protection; Chemistry; Ecology; Biology; Medicine; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002109115,0.00005224908,0.00003925459,0.00001512478,0.0000622489,0.00006275095,0.00004647251,0.00001748919,0.00008370135],"category_scores_gemma":[0.000004657306,0.0000386072,0.00001029436,0.0001024089,0.00003058972,0.0001342754,0.00002878,0.00006523847,0.00001296879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002444106,"about_ca_system_score_gemma":0.00001028853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002361638,"about_ca_topic_score_gemma":0.00003411729,"domain_scores_codex":[0.999581,0.000005707397,0.0001116728,0.0001333885,0.00005843686,0.0001098349],"domain_scores_gemma":[0.9998601,0.00001781481,0.00001059829,0.0000871814,0.000001213945,0.00002309545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001845136,0.00001346835,0.0004391759,0.0001676903,0.00001061209,0.000003104943,0.006976144,0.005506038,0.9011928,0.03062822,0.0003365926,0.05472434],"study_design_scores_gemma":[0.0007869987,0.00004098988,0.06068626,0.0003869988,0.00002734199,0.0002208723,0.02589871,0.6737307,0.1050153,0.02177249,0.1105029,0.0009303637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8123055,0.0008816071,0.1696617,0.01094356,0.000110688,0.0002914378,0.000001845638,0.000174435,0.005629204],"genre_scores_gemma":[0.9994831,0.00009345308,0.000159331,0.00002340938,0.0000130534,0.00001423787,0.00001201088,0.000006152259,0.0001952173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7961775,"threshold_uncertainty_score":0.1574356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364161060214352,"score_gpt":0.254425644214773,"score_spread":0.2307840336126295,"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."}}