{"id":"W2055339408","doi":"10.1002/elsc.200620120","title":"Specific Treatment Technologies for Removing Arsenic from Water","year":2006,"lang":"en","type":"article","venue":"Engineering in Life Sciences","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Arsenic; Metalloid; Adsorption; Water treatment; Nanofiltration; Chemistry; Environmental chemistry; Filtration (mathematics); Contamination; Surface water; Ion exchange; Environmental engineering; Membrane; Environmental science; Ion; Metal","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001387121,0.00007396713,0.00006873409,0.00005787405,0.0000714839,0.00002061986,0.0001223752,0.00003229827,0.0001103736],"category_scores_gemma":[0.00002782867,0.00005353111,0.00002441653,0.0001393229,0.00008773992,0.0001513899,0.00003378332,0.00002676528,0.00004701921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001273059,"about_ca_system_score_gemma":0.000004875573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002306805,"about_ca_topic_score_gemma":0.00008757967,"domain_scores_codex":[0.9993619,0.00000452183,0.000126124,0.0002095348,0.000111304,0.0001865572],"domain_scores_gemma":[0.999827,0.00005680005,0.00001710373,0.00008202109,0.000001852661,0.00001523451],"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":[0.00001152505,0.0001541573,0.07647949,0.000008196774,0.000008453203,0.000008467325,0.001634643,0.4807335,0.3516095,0.004158307,0.002349323,0.08284443],"study_design_scores_gemma":[0.001753126,0.0003196679,0.2367458,0.00005987461,0.0000111297,0.000004167164,0.001136272,0.2592388,0.3242061,0.00615807,0.1695942,0.0007726901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916345,0.0001026375,0.005703001,0.0005151662,0.0001535419,0.0001559873,0.000002043111,0.0001352129,0.001597944],"genre_scores_gemma":[0.9908898,0.00001619826,0.008735936,0.00001055773,0.00003753367,0.00002965361,0.00000526353,0.000004105665,0.0002709074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2214947,"threshold_uncertainty_score":0.2182935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022669516909611,"score_gpt":0.2007871285065886,"score_spread":0.1905604333374925,"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."}}