{"id":"W3023425702","doi":"10.1002/opfl.1369","title":"Biological Ion Exchange Provides DOC Removal in Small Communities","year":2020,"lang":"en","type":"article","venue":"Opflow","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ion exchange; Process (computing); Environmental science; Computer science; Chemistry; Ion","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005091364,0.0004301585,0.0003594059,0.0004739158,0.002642754,0.001937891,0.0006152719,0.0007288137,0.001682955],"category_scores_gemma":[0.0006030211,0.0001815095,0.00033537,0.000316123,0.0006597096,0.0007076889,0.001398733,0.0005808026,0.0006092623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002633825,"about_ca_system_score_gemma":0.003938571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1506915,"about_ca_topic_score_gemma":0.3061081,"domain_scores_codex":[0.9996178,0.00003781081,0.000007920989,0.00007264838,0.0001260108,0.000137918],"domain_scores_gemma":[0.9996163,0.00004245217,0.00002085457,0.00002082295,0.0001732953,0.0001263666],"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":[0.0003169347,0.0003200847,0.01019036,0.0003476836,0.00003979237,0.000430979,0.000530181,0.001810898,0.897043,0.00109271,0.002826374,0.08505096],"study_design_scores_gemma":[0.0002626831,0.00193204,0.07071666,0.0001636541,0.000196932,0.0008888794,0.004300148,0.01841608,0.8108,0.003105912,0.08907682,0.000140223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9679446,0.0009860734,0.009596638,0.001272616,0.0001098177,0.0002402673,0.0001660963,0.0003851702,0.0192986],"genre_scores_gemma":[0.977521,0.0009141907,0.0107059,0.000253642,0.00001606927,0.00006831768,0.0001311102,0.0000310982,0.01035865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1506915,"threshold_uncertainty_score":0.2996288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05615238603073096,"score_gpt":0.2271784878486977,"score_spread":0.1710261018179667,"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."}}