{"id":"W2006560384","doi":"10.1016/j.jhazmat.2011.03.070","title":"Biosorption of arsenic from contaminated water by anaerobic biomass","year":2011,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University; U.S. Environmental Protection Agency","keywords":"Arsenate; Arsenic; Biosorption; Arsenite; Chemistry; Biomass (ecology); Environmental chemistry; Wastewater; Leaching (pedology); Freundlich equation; Langmuir; Adsorption; Pulp and paper industry; Desorption; Environmental engineering; Sorption; Environmental science; Geology; Soil science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001936416,0.0004126952,0.0003105939,0.0003256047,0.000357384,0.0004873036,0.000227917,0.0002750184,0.001301551],"category_scores_gemma":[0.0001931898,0.0001768721,0.0002556116,0.0002351277,0.0001826661,0.0002753639,0.0003520121,0.0003663384,0.0003243514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002857688,"about_ca_system_score_gemma":0.0003162195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003248013,"about_ca_topic_score_gemma":0.002977561,"domain_scores_codex":[0.9998679,0.00001995057,0.000007421643,0.0000162018,0.00004516894,0.00004333263],"domain_scores_gemma":[0.9999346,0.00001644901,0.000008746117,0.000004639759,0.00001960829,0.00001607222],"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":[0.0003023817,0.00005118419,0.0006804445,0.00003356828,0.000008839706,0.00006422165,0.00005880397,0.0004971691,0.9959356,0.0001154515,0.00004492364,0.002207528],"study_design_scores_gemma":[0.00001986383,0.0004360917,0.00287008,0.000007056144,0.00001303368,0.000059603,0.0001878518,0.002729398,0.9927182,0.000128554,0.0008212661,0.000008960316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986003,0.0001050189,0.000496709,0.00002639837,0.00001269961,0.000003731508,0.00004360402,0.00000774122,0.0007038168],"genre_scores_gemma":[0.9971218,0.0001841209,0.0004316657,0.00000959188,0.000005322098,0.000002922692,0.00009612627,0.000005684763,0.002142763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003248013,"threshold_uncertainty_score":0.006458223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093845978977805,"score_gpt":0.1927709474454823,"score_spread":0.1818324876557043,"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."}}