{"id":"W1577315848","doi":"10.1002/j.1551-8833.2000.tb09023.x","title":"Conventional and optimized coagulation for NOM removal","year":2000,"lang":"en","type":"article","venue":"American Water Works Association","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"American Water (Canada)","funders":"","keywords":"Coagulation; Turbidity; Chemistry; Water treatment; Total organic carbon; Pulp and paper industry; Activated carbon; Flocculation; Chromatography; Waste management; Environmental engineering; Environmental science; Environmental chemistry; Adsorption; Organic chemistry; Engineering; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004376662,0.0003581484,0.0004009228,0.0003771756,0.0002404092,0.0004565367,0.0002810629,0.0004152813,0.001295659],"category_scores_gemma":[0.0005523765,0.0001842357,0.0003550307,0.0003389182,0.000220562,0.0002551353,0.0002445108,0.0003240612,0.0003658733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005347031,"about_ca_system_score_gemma":0.000476866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00135577,"about_ca_topic_score_gemma":0.002987183,"domain_scores_codex":[0.9994235,0.00008267333,0.00005298682,0.0001324592,0.0002204645,0.00008792803],"domain_scores_gemma":[0.9998141,0.00004501463,0.00003837515,0.00001997748,0.00006777788,0.00001478017],"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":[0.0002251543,0.00005013974,0.0003379206,0.0001459061,0.00002200898,0.00004881988,0.000033808,0.0009731126,0.9934177,0.0001389718,0.0002342036,0.004372138],"study_design_scores_gemma":[0.00003623395,0.0004556543,0.003243626,0.000008188033,0.00004040012,0.0001459048,0.00002627172,0.003130206,0.9898556,0.00007571974,0.002961461,0.00002071054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792139,0.002241806,0.01386241,0.00009430738,0.00008070586,0.0001661303,0.000453422,0.0001866745,0.003700753],"genre_scores_gemma":[0.9589041,0.001967714,0.03476364,0.0001007948,0.00004236048,0.0001596147,0.0006167114,0.00006290396,0.003382044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00135577,"threshold_uncertainty_score":0.00433439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004267672328133662,"score_gpt":0.2072268554424997,"score_spread":0.2029591831143661,"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."}}