{"id":"W3176188453","doi":"10.1089/ees.2020.0372","title":"Enhanced Coagulation for Removal of Natural Organic Matter and Disinfection Byproducts: Multivariate Optimization","year":2021,"lang":"en","type":"article","venue":"Environmental Engineering Science","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Dissolved organic carbon; Coagulation; Settling; Flocculation; Chemistry; Water treatment; Sedimentation; Natural organic matter; Mixing (physics); Fractionation; Pulp and paper industry; Environmental chemistry; Haloacetic acids; Organic matter; Dewatering; Settling time; Trihalomethane; Environmental science; Environmental engineering; Chromatography; Sediment","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001078443,0.0008619986,0.0007968734,0.0004796743,0.0001729302,0.0005767907,0.0003738245,0.0003480382,0.0004418487],"category_scores_gemma":[0.0009752259,0.000196996,0.001191909,0.0006324874,0.0002020113,0.0003088423,0.0003334488,0.0005059576,0.0001131141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004718373,"about_ca_system_score_gemma":0.0006107832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002853257,"about_ca_topic_score_gemma":0.002975362,"domain_scores_codex":[0.9994591,0.0001402449,0.00004072541,0.0001204713,0.0001991644,0.00004030138],"domain_scores_gemma":[0.9997913,0.00009777128,0.00003773447,0.00001216956,0.00005202602,0.000008864296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007581244,0.001336277,0.008659948,0.0007831927,0.0004213628,0.0001298813,0.000171577,0.1620113,0.722627,0.000913984,0.0003272668,0.1018601],"study_design_scores_gemma":[0.00008623112,0.00174302,0.01936977,0.00002527357,0.0002331328,0.0001292898,0.00008738531,0.5469927,0.4281878,0.0004923186,0.002576267,0.00007695903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8661667,0.00169977,0.1297537,0.0001191116,0.00001577087,0.0002229409,0.000461386,0.0003524029,0.001208201],"genre_scores_gemma":[0.8909141,0.001517525,0.1051396,0.00005623556,0.00001301735,0.0003281575,0.0008186135,0.00004547644,0.00116733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002853257,"threshold_uncertainty_score":0.00570339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00278080609804698,"score_gpt":0.1793077813116347,"score_spread":0.1765269752135877,"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."}}