{"id":"W18594006","doi":"10.2166/wqrj.2006.019","title":"Iron-Coated Sponge as Effective Media to Remove Arsenic from Drinking Water","year":2006,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Arsenic; Adsorption; Environmental chemistry; Chemistry; Water treatment; Effluent; Filtration (mathematics); Contamination; Water quality; Groundwater; Arsenic contamination of groundwater; Environmental science; Ion exchange; Environmental engineering; Waste management; Ion; Geology; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001369401,0.0003261431,0.0001525432,0.0003040637,0.0001182978,0.0001507809,0.000199776,0.0002389387,0.0008266254],"category_scores_gemma":[0.0001496267,0.0001170983,0.0001965884,0.00008677228,0.0001557726,0.0001570869,0.0001174725,0.0002022735,0.0002265149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250212,"about_ca_system_score_gemma":0.0001167653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005538801,"about_ca_topic_score_gemma":0.0008414304,"domain_scores_codex":[0.9999273,0.00001562925,0.000003786468,0.0000112988,0.00003129815,0.00001066132],"domain_scores_gemma":[0.999895,0.00002820774,0.00002482766,0.000005154628,0.00002365262,0.00002320619],"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":[0.00007728906,0.00002497725,0.0001080446,0.00007603111,0.00000490776,0.00007962811,0.000008171495,0.00007426383,0.9973071,0.00004044958,0.00008201558,0.002117208],"study_design_scores_gemma":[0.00001648503,0.0005462765,0.001118379,0.000007546642,0.00001784729,0.0001523107,0.00001303828,0.00099321,0.9947677,0.0000159631,0.002345381,0.000005853998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987029,0.002420582,0.006571299,0.0001534739,0.0001204876,0.00006307659,0.0001195233,0.000197207,0.00332539],"genre_scores_gemma":[0.9878684,0.0008860756,0.007478945,0.00006971911,0.00002239093,0.00001948468,0.0001271801,0.00001567434,0.003512206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008266254,"threshold_uncertainty_score":0.002765357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03749262467015025,"score_gpt":0.3453773231676006,"score_spread":0.3078846984974503,"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."}}