{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004929401,0.0001078428,0.0001343338,0.000153139,0.0001660367,0.00009726203,0.0002759111,0.00001657647,0.00003862752],"category_scores_gemma":[3.519658e-7,0.00006345941,0.00001669324,0.0001874066,0.00007869668,0.0002634751,0.000266823,0.000068344,0.00001183465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005626271,"about_ca_system_score_gemma":0.00000402776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005865889,"about_ca_topic_score_gemma":0.000001583067,"domain_scores_codex":[0.9989108,0.00002560962,0.000230075,0.0002137549,0.0003045654,0.0003152279],"domain_scores_gemma":[0.9996664,0.000002250469,0.00001400376,0.0002274006,0.00003645062,0.00005348014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002005232,0.00006164622,0.003071019,0.0009394639,0.0001300266,0.00007401056,0.01773652,0.6647302,0.306159,0.001246734,0.00540749,0.0004238272],"study_design_scores_gemma":[0.0007430657,0.0001727495,0.0007184263,0.0001114083,0.00004798569,0.0001032875,0.003659889,0.3334765,0.6137994,0.00007558623,0.0464625,0.0006292309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949198,0.00009809907,0.001305788,0.00003928408,0.00109318,0.0002461546,0.00001073663,0.0001062191,0.002180683],"genre_scores_gemma":[0.9978436,0.000005554494,0.0002994294,0.000006121506,0.00001594012,0.00004885048,0.00002489945,0.00001387666,0.001741695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3312537,"threshold_uncertainty_score":0.25878,"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."}}