{"id":"W4300967501","doi":"10.1002/aws2.1309","title":"Integrated asset management of urban water and wastewater systems","year":2022,"lang":"en","type":"article","venue":"AWWA Water Science","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wastewater; Asset management; Asset (computer security); Integrated business planning; Mains electricity; Business; Service (business); Capital (architecture); Integrated water resources management; Environmental economics; Water supply; Water resources; Environmental science; Finance; Computer science; Environmental engineering; Engineering; Economics; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000673694,0.0003910206,0.0004946035,0.001024313,0.0004401634,0.001735809,0.000633823,0.0004007197,0.001765048],"category_scores_gemma":[0.001573569,0.0002443875,0.0002872876,0.001206475,0.0004252175,0.001188012,0.001178795,0.0003661959,0.0001189811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212716,"about_ca_system_score_gemma":0.001693183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04228351,"about_ca_topic_score_gemma":0.03856805,"domain_scores_codex":[0.9995369,0.0001428346,0.0000247206,0.00008054775,0.0001304006,0.00008474515],"domain_scores_gemma":[0.9995511,0.0001774052,0.00008059884,0.00003441049,0.0001085845,0.0000479283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003347467,0.00003844022,0.004515314,0.00001463485,0.00002825422,0.00007167421,0.00004607348,0.9646855,0.0008707803,0.003853439,0.0002060114,0.02563631],"study_design_scores_gemma":[0.000006905674,0.00001759599,0.001101207,0.000002878837,0.000007919479,0.000007870427,0.0000455281,0.9951919,0.0005562222,0.002580456,0.0004771491,0.00000431651],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6156695,0.000214053,0.3739419,0.000288012,0.00001454834,0.0001452175,0.0005113314,0.0005200012,0.008695456],"genre_scores_gemma":[0.9868686,0.00004300882,0.01219033,0.000006643777,0.000002237022,0.00002220792,0.0001140409,0.000008831475,0.0007441058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04228351,"threshold_uncertainty_score":0.0840748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007195797011934113,"score_gpt":0.1734972508532397,"score_spread":0.1663014538413056,"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."}}