{"id":"W2331033828","doi":"10.1021/es201498v","title":"The Impact of Metallic Coagulants on the Removal of Organic Compounds from Oil Sands Process-Affected Water","year":2011,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Alberta","funders":"Alberta Innovates; King Saud University; Canada Research Chairs; Chinese Academy of Sciences; University of Alberta; Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Flocculation; Chemistry; Alum; Turbidity; Adsorption; Cationic polymerization; Oil sands; Environmental chemistry; Coagulation; Polymer; Water treatment; Chemical engineering; Environmental engineering; Materials science; Organic chemistry; Asphalt; Environmental science; Geology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002693021,0.0001456291,0.0002136419,0.0001071647,0.0003242332,0.0000147015,0.001065185,0.0001033639,0.0007986768],"category_scores_gemma":[0.00004601228,0.00006530104,0.00009100601,0.0004257919,0.002783604,0.0000692789,0.0001799284,0.0002042969,0.0000258581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001040247,"about_ca_system_score_gemma":0.00003652409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007268476,"about_ca_topic_score_gemma":0.000006960304,"domain_scores_codex":[0.9987979,0.00001622095,0.0002238052,0.0002922946,0.0003466035,0.0003231642],"domain_scores_gemma":[0.9992244,0.00003611896,0.0001689257,0.0005219843,0.00001046032,0.00003812926],"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":[0.00001900027,0.0001366542,0.007202012,0.000003060637,0.00005458665,0.000003725947,0.0002493844,0.000003004132,0.9880857,0.00002105002,0.00000248993,0.00421926],"study_design_scores_gemma":[0.0001617415,0.00007823661,0.00370847,0.000019054,0.00003854076,0.00002122423,0.0006621609,0.0001565991,0.9942408,0.0007577955,0.00006722003,0.00008818962],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939582,0.000170292,0.000003540995,0.00009053696,0.00001248972,0.000007502652,0.00001470984,0.00003947752,0.005703294],"genre_scores_gemma":[0.9993191,0.00004946023,0.00003311956,0.000007459915,0.000008223486,0.00000653417,0.000006108642,0.000009299024,0.0005607373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006154995,"threshold_uncertainty_score":0.9999303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058616173980004,"score_gpt":0.2280654004588952,"score_spread":0.2174792387190952,"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."}}