{"id":"W2001732627","doi":"10.2166/wst.2007.589","title":"Solving the inverse problem for aggregation in activated sludge flocculation using a population balance framework","year":2007,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vlaamse regering; Universiteit Gent; Canada Research Chairs","keywords":"Flocculation; Inverse problem; Similarity (geometry); Population; Inverse; Mathematical optimization; Property (philosophy); Balance (ability); Mathematics; Computer science; Applied mathematics; Biological system; Engineering; Environmental engineering; Artificial intelligence; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001185431,0.0001113674,0.0001120501,0.0003857194,0.0005975324,0.00004505999,0.0002730978,0.0001262968,0.00004352948],"category_scores_gemma":[0.0001729414,0.00007634173,0.00002646736,0.002014095,0.0005157316,0.0005412248,0.0002158058,0.0001372378,0.0000216204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004124388,"about_ca_system_score_gemma":0.00001063405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001766258,"about_ca_topic_score_gemma":0.0005577222,"domain_scores_codex":[0.9986046,0.0000169868,0.0002974253,0.000368554,0.0002851971,0.0004272499],"domain_scores_gemma":[0.9995213,0.00004853032,0.0001057996,0.0002542732,0.00003978654,0.00003033836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002513736,0.00002863873,0.6497535,0.000004693874,0.000002354246,9.11098e-7,0.001946521,0.02803969,0.3012502,0.001792407,0.00001850317,0.01713755],"study_design_scores_gemma":[0.0005442223,0.00004820047,0.5578947,0.00005532116,0.00001161681,0.00001151103,0.0007552207,0.2589098,0.1327719,0.04650437,0.00214143,0.0003517067],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8894718,0.000007536786,0.108616,0.0009592121,0.0001264819,0.0005122576,5.404888e-7,0.00009490261,0.0002112813],"genre_scores_gemma":[0.9792105,0.000001602211,0.02056898,0.0001283265,0.00002033342,0.00002645507,0.00000424981,0.000007116675,0.0000324413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2308701,"threshold_uncertainty_score":0.4595796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0206284319081351,"score_gpt":0.2802628472295414,"score_spread":0.2596344153214063,"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."}}