{"id":"W2065964685","doi":"10.1016/j.watres.2006.03.002","title":"Long-term storage conditions for carriers with denitrifying biomass of the fluidized, methanol-fed denitrification reactor of the Montreal Biodome, and the impact on denitrifying activity and bacterial population","year":2006,"lang":"en","type":"article","venue":"Water Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Biodome; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Denitrifying bacteria; Denitrification; Nitrate; Glycerol; Nitrite; Population; Chemistry; Biomass (ecology); Fluidized bed; Environmental chemistry; Environmental engineering; Environmental science; Ecology; Biology; Nitrogen; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005176527,0.000466564,0.0003628164,0.0002135723,0.000665924,0.0009315778,0.000620884,0.0005806576,0.001814369],"category_scores_gemma":[0.0007455439,0.0002080023,0.0003993625,0.0002533998,0.0003500251,0.000956981,0.000289865,0.0005354987,0.0003561958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002370324,"about_ca_system_score_gemma":0.001056364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02984252,"about_ca_topic_score_gemma":0.04380331,"domain_scores_codex":[0.9997359,0.00003775481,0.00001765729,0.00006789575,0.00005340626,0.00008736231],"domain_scores_gemma":[0.99965,0.00006134489,0.0000632461,0.00002638119,0.0001525799,0.00004650746],"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":[0.00120046,0.000133105,0.001681872,0.0000442785,0.00001954174,0.0000571968,0.0001335829,0.0004339552,0.9928785,0.0001041932,0.000186444,0.003126943],"study_design_scores_gemma":[0.00003246422,0.0007898796,0.008229761,0.00001359387,0.00004990855,0.00006177606,0.0002672285,0.002115623,0.9872165,0.00006250748,0.001124318,0.0000364662],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986531,0.0003950634,0.0003385096,0.00007104196,0.00002417095,0.000008118351,0.0003121122,0.00001450515,0.0001834916],"genre_scores_gemma":[0.9969187,0.0001748886,0.000449865,0.00002678192,0.00001087769,0.00001703064,0.0006948918,0.00001503515,0.00169183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02984252,"threshold_uncertainty_score":0.05933768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03021910183356373,"score_gpt":0.3022451905588747,"score_spread":0.272026088725311,"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."}}