{"id":"W3092024966","doi":"10.1016/j.biortech.2020.124223","title":"Acclimatization of microbial community of submerged membrane bioreactor treating hospital wastewater","year":2020,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre de Recherche Industrielle du Québec; Université de Montréal; GDG Environnement; Armand Frappier Museum; Centre Hospitalier de l’Université de Montréal; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Acclimatization; Wastewater; Microbial population biology; Bioreactor; Biology; Sewage treatment; Environmental science; Pulp and paper industry; Environmental engineering; Ecology; Bacteria; Botany; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001911541,0.0004265391,0.0003860049,0.0001905901,0.0002218109,0.0003808886,0.0002605919,0.0003677063,0.001068837],"category_scores_gemma":[0.0004004667,0.0001618233,0.0004297667,0.0002408552,0.0001708492,0.0003298646,0.0003521941,0.0004115422,0.0002302765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002884046,"about_ca_system_score_gemma":0.0004142123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873618,"about_ca_topic_score_gemma":0.001847663,"domain_scores_codex":[0.9997492,0.00003150762,0.00002436297,0.00006916367,0.00005975926,0.00006601462],"domain_scores_gemma":[0.9998807,0.00002213348,0.00002123736,0.00001439621,0.00003753982,0.00002397572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008527871,0.00002309628,0.000328051,0.00001795088,0.00000297383,0.00001933447,0.00003106385,0.00003438097,0.9986462,0.00001024111,0.00001196946,0.0007894834],"study_design_scores_gemma":[0.00002055472,0.0008499585,0.04435686,0.0000150606,0.00003617287,0.0001928676,0.0003229221,0.001062295,0.9517505,0.00009188121,0.001280071,0.0000208453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983249,0.0001896854,0.0007384497,0.00004728885,0.00003323577,0.00001696153,0.000202347,0.000019045,0.0004281048],"genre_scores_gemma":[0.9971866,0.0001598204,0.001001663,0.00005491332,0.00001158041,0.00003371898,0.0004036859,0.000008220671,0.001139839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001873618,"threshold_uncertainty_score":0.00372541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01196386660741686,"score_gpt":0.1995156340377517,"score_spread":0.1875517674303348,"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."}}