{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001938431,0.000351891,0.0002836488,0.0006441167,0.0001926802,0.0003579748,0.00024872,0.0004792908,0.000706974],"category_scores_gemma":[0.0002454137,0.0001046543,0.0004470923,0.0005635749,0.0001259164,0.0002387394,0.0001227844,0.0002544054,0.0001963807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003659809,"about_ca_system_score_gemma":0.0001783706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001832333,"about_ca_topic_score_gemma":0.003826181,"domain_scores_codex":[0.9997391,0.00002881671,0.00001623996,0.00003318314,0.0001559855,0.00002666887],"domain_scores_gemma":[0.9998806,0.00002713811,0.00001440213,0.000008794363,0.00005647977,0.00001256002],"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":[0.0002046598,0.000107787,0.0005122234,0.0004602247,0.00002476343,0.00006788489,0.00001466121,0.001515668,0.9859897,0.0001147863,0.00007790043,0.01090981],"study_design_scores_gemma":[0.00001281989,0.0007927715,0.005948046,0.00001270371,0.00003927227,0.0001329439,0.00003953309,0.004831035,0.9848045,0.00005932487,0.003307088,0.00001992501],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886918,0.006122275,0.002583954,0.00007201937,0.00002987135,0.00005114932,0.0003472814,0.00004219693,0.002059508],"genre_scores_gemma":[0.9835275,0.004603257,0.009106526,0.00002663469,0.0000162798,0.00004103989,0.0004955513,0.00001805594,0.002165141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001832333,"threshold_uncertainty_score":0.003643274,"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."}}