{"id":"W2026462921","doi":"10.1016/j.watres.2007.06.019","title":"A new plant-wide modelling methodology for WWTPs","year":2007,"lang":"en","type":"article","venue":"Water Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Eusko Jaurlaritza; Canada Research Chairs","keywords":"Process modeling; Process (computing); Transformation (genetics); Computer science; Unit operation; Biochemical engineering; Engineering; Environmental engineering; Process optimization","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003153377,0.0001055196,0.0001309273,0.00009920127,0.0002039511,0.00003559553,0.0002689086,0.00008226624,0.0008706094],"category_scores_gemma":[0.0000230314,0.00006785669,0.00006546588,0.0001164177,0.00007761001,0.0001002848,0.0002225838,0.0001600263,0.001326406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205184,"about_ca_system_score_gemma":0.00001031581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00149987,"about_ca_topic_score_gemma":0.0002199098,"domain_scores_codex":[0.9980433,0.000137725,0.0001656128,0.0003308661,0.0003903082,0.0009322026],"domain_scores_gemma":[0.9993806,0.0001808965,0.00001106054,0.0002124357,0.00001220676,0.0002027753],"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":[0.001654714,0.0001697649,0.01515244,0.00003215712,0.0001007644,0.0002259028,0.00567247,0.003780384,0.9202808,0.0004650863,0.03043978,0.02202573],"study_design_scores_gemma":[0.0006474711,0.0001889474,0.0002001985,0.000004879007,0.000008437152,0.00002033949,0.000139521,0.001962551,0.9265436,0.01385887,0.05629469,0.0001304816],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8290296,0.00002983614,0.1673949,0.0006245875,0.0000786638,0.0004274884,0.000004453091,0.00003236431,0.002378094],"genre_scores_gemma":[0.6046543,0.000008266187,0.3719649,0.00007300586,0.0001849972,0.00002725612,0.0000453022,0.00003134941,0.02301058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2243753,"threshold_uncertainty_score":0.9994512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2527229447079429,"score_gpt":0.3854607835576023,"score_spread":0.1327378388496595,"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."}}