{"id":"W3195619727","doi":"10.3390/w13162244","title":"Low Cost Activated Carbon for Removal of NOM and DBPs: Optimization and Comparison","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland; Royal Bank of Canada","keywords":"Adsorption; Chemistry; Activated carbon; Natural organic matter; Nitric acid; Water treatment; Dissolved organic carbon; Metal; Nuclear chemistry; Portable water purification; Environmental chemistry; Inorganic chemistry; Environmental engineering; Organic chemistry; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005725152,0.00006000637,0.00009549677,0.0000128577,0.00003589577,0.0000151289,0.00002371058,0.00004573281,0.0003441823],"category_scores_gemma":[0.000005541505,0.00004359156,0.00001553047,0.00004194905,0.00007938963,0.00006367839,0.00005385813,0.00002961384,0.000004692061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001917222,"about_ca_system_score_gemma":0.000002429402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002255865,"about_ca_topic_score_gemma":0.00001746295,"domain_scores_codex":[0.9995414,0.00001664988,0.0001172288,0.0001459725,0.00007821612,0.0001005079],"domain_scores_gemma":[0.9998479,0.000008234188,0.00003090043,0.00006426129,0.000008892807,0.00003984038],"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":[0.00005170147,0.00005545501,0.00372279,0.00001536786,0.000007818283,0.000003863795,0.000298064,0.002172005,0.9886059,0.00002224066,0.0001039922,0.004940835],"study_design_scores_gemma":[0.0007558445,0.0000459596,0.003059737,0.0000117916,0.00001525638,0.00006658921,0.000116991,0.05749901,0.9292197,0.00005651897,0.009029113,0.0001234466],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969045,0.00001443061,0.001497554,0.0002813152,0.00004721311,0.0001333025,0.0000102599,0.00001222315,0.001099195],"genre_scores_gemma":[0.9953052,0.00001620731,0.003360259,0.00006950903,0.00001251663,0.000002500485,0.00003152197,0.000005759756,0.001196559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05938612,"threshold_uncertainty_score":0.3768555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317038787439293,"score_gpt":0.2350387331807772,"score_spread":0.2218683453063843,"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."}}