{"id":"W1855124810","doi":"10.1016/j.watres.2015.05.015","title":"Fast formation of aerobic granules by combining strong hydraulic selection pressure with overstressed organic loading rate","year":2015,"lang":"en","type":"article","venue":"Water Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":143,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Granulation; Granule (geology); Bioreactor; Settling; Chemistry; Settling time; Pulp and paper industry; Continuous stirred-tank reactor; Volumetric flow rate; Hydraulic retention time; Materials science; Waste management; Chemical engineering; Environmental engineering; Environmental science; Composite material; Sewage treatment; Engineering; Thermodynamics","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":[0.0001363146,0.0003905123,0.0003388323,0.00009471679,0.0001086259,0.0004006384,0.0001789972,0.000226931,0.000584069],"category_scores_gemma":[0.000278577,0.0001595825,0.0002063011,0.0001205531,0.0001740355,0.0002472633,0.0005236287,0.0002861783,0.0001133817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001591626,"about_ca_system_score_gemma":0.0002051661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004791711,"about_ca_topic_score_gemma":0.0007892423,"domain_scores_codex":[0.9998642,0.00001287001,0.00001466594,0.00003128511,0.00003752252,0.00003943807],"domain_scores_gemma":[0.9998424,0.0000293765,0.00003904059,0.00002279994,0.00001543369,0.00005088862],"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":[0.00007145051,0.00001111653,0.0001748893,0.00001622188,0.000003795115,0.00002131312,0.00001369118,0.00007089914,0.9983425,0.00002718906,0.00003906617,0.001207847],"study_design_scores_gemma":[0.00001700892,0.0001063604,0.002428412,0.000002306544,0.0000076868,0.00003905106,0.0000155532,0.001367527,0.9953749,0.00003144998,0.0006027624,0.000006984536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958695,0.0002066354,0.003177966,0.00007840581,0.00003756728,0.00002174964,0.00008897447,0.0001243606,0.0003948518],"genre_scores_gemma":[0.9981792,0.00009441515,0.001176859,0.00002588831,0.000008030324,0.00001626567,0.00007232878,0.00001913901,0.0004078869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000584069,"threshold_uncertainty_score":0.0019539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03527188345322235,"score_gpt":0.2669436661328761,"score_spread":0.2316717826796537,"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."}}