{"id":"W2001300966","doi":"10.1016/j.watres.2005.10.029","title":"Design optimization of a self-cleaning moving-bed bioreactor for seawater denitrification","year":2005,"lang":"en","type":"article","venue":"Water Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Montreal Biodome; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Denitrification; Bioreactor; Seawater; Moving bed biofilm reactor; Packed bed; Environmental engineering; Chemistry; TRACER; Biofilm; Environmental science; Environmental chemistry; Chromatography; Nitrogen; Ecology; Bacteria; 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":[],"consensus_categories":[],"category_scores_codex":[0.0009475586,0.000103342,0.0001099186,0.0001115352,0.000164258,0.00004762147,0.0002163721,0.00006733985,0.0006290855],"category_scores_gemma":[0.00001559416,0.00006915715,0.00004794804,0.0001576481,0.00008408868,0.0002604069,0.0001076479,0.00008114481,0.0003799159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001943597,"about_ca_system_score_gemma":0.00001089387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033256,"about_ca_topic_score_gemma":0.000007676236,"domain_scores_codex":[0.9985023,0.0001604051,0.0002030007,0.0002751765,0.000415221,0.0004439073],"domain_scores_gemma":[0.9995844,0.00003870164,0.00003013113,0.0002194967,0.0000501414,0.00007715027],"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":[0.0001878529,0.0002215116,0.001832189,0.00001683965,0.00003050159,0.000001988629,0.002331247,0.01685482,0.9757655,0.00001108316,0.0005564372,0.002190077],"study_design_scores_gemma":[0.0005518937,0.0001521841,0.0001366939,0.000006214671,0.00001284016,0.00000305294,0.00006696912,0.05522632,0.9422907,0.00008527385,0.001376029,0.00009188263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813885,0.00001309719,0.01683148,0.0004321749,0.00002081701,0.0008907012,0.000002796473,0.000052852,0.0003675683],"genre_scores_gemma":[0.8332263,0.000006212237,0.1657164,0.000009714646,0.0000507157,0.00008371127,0.00003783505,0.00002145001,0.0008476108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1488849,"threshold_uncertainty_score":0.6888044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06245675919266827,"score_gpt":0.3031131814336063,"score_spread":0.240656422240938,"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."}}