{"id":"W4365397217","doi":"10.2139/ssrn.4417073","title":"Dynamic Performance Simulation and Treatment Alternatives Evaluation for Process Intensification for a Wastewater Treatment Plant in Toronto","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Process (computing); Sewage treatment; Environmental science; Wastewater; Process engineering; Computer science; Engineering; Environmental engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003818156,0.0002832924,0.0003893421,0.0003061513,0.0002386175,0.000223496,0.0002944025,0.0001648076,0.00001149975],"category_scores_gemma":[0.0003343567,0.00020173,0.0001606248,0.0001322204,0.00003035857,0.000296658,0.00004366748,0.000252143,0.000003408105],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006947393,"about_ca_system_score_gemma":0.00125047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002613987,"about_ca_topic_score_gemma":0.008649752,"domain_scores_codex":[0.9970279,0.0001084247,0.0008635696,0.0006663914,0.0005578353,0.0007759072],"domain_scores_gemma":[0.9975557,0.0006865791,0.0006481417,0.0003593019,0.0006935386,0.0000567729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006342264,0.000288223,0.002533952,0.00003212148,0.0002142654,2.034729e-7,0.003518464,0.3573099,0.0001540864,0.004292118,0.00001337491,0.6310091],"study_design_scores_gemma":[0.001128837,0.0006942214,0.002090354,0.0000472082,0.00006985648,0.000005764284,0.002565063,0.7527159,0.0001796163,0.2400439,0.0003009773,0.0001582571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9314659,0.0007344613,0.06241569,0.0008151093,0.0001910173,0.004172551,0.0001290974,0.00005400717,0.00002211995],"genre_scores_gemma":[0.9924929,0.002850965,0.0007052753,0.000009148088,0.0001181975,0.002723452,0.0003154833,0.00003476644,0.000749859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6308509,"threshold_uncertainty_score":0.9968647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1644997938406942,"score_gpt":0.4783889662844869,"score_spread":0.3138891724437927,"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."}}