{"id":"W4405835833","doi":"10.1007/698_2024_1195","title":"Strategic Decision-Making in Water Utilities: Historical Insights and Emerging Analytics for Water Mains Repair Versus Replacement Decision","year":2024,"lang":"en","type":"book-chapter","venue":"˜The œhandbook of environmental chemistry","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Analytics; Mains electricity; Water utility; Electricity; Business; Computer science; Environmental economics; Environmental science; Water supply; Engineering; Data science; Economics; Environmental engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001479713,0.0003889866,0.0004049118,0.00008575086,0.00006916267,0.00003489765,0.0001502341,0.0003169942,0.0002460925],"category_scores_gemma":[0.000001840278,0.0002555205,0.0001880609,0.00001236128,0.00006625276,0.00005853012,0.0001309359,0.0002631186,0.00001304513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009795949,"about_ca_system_score_gemma":0.000007382223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003477386,"about_ca_topic_score_gemma":0.00003293662,"domain_scores_codex":[0.998306,0.000004324174,0.0006780166,0.0004329974,0.0003008949,0.0002777528],"domain_scores_gemma":[0.9993622,0.0001076924,0.00005761316,0.0004039422,0.000007515374,0.00006109574],"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":[0.01335917,0.001002635,0.0003244891,0.03083783,0.008379424,0.001332516,0.04224236,0.5590578,0.2968478,0.002704178,0.02769603,0.01621582],"study_design_scores_gemma":[0.008540443,0.0008423079,0.00001228201,0.0146304,0.001529552,0.0001306057,0.002427753,0.2915892,0.1223927,0.04389144,0.5096588,0.004354554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5363401,0.07579209,0.02236801,0.00007866871,0.007124458,0.004982753,0.0005916183,0.0009085799,0.3518137],"genre_scores_gemma":[0.9281186,0.0008444113,0.0007030158,0.000006562273,0.0002256272,0.00004515299,0.0001427396,0.0001446436,0.06976924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4819627,"threshold_uncertainty_score":0.9999897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250175769249822,"score_gpt":0.2028230659984233,"score_spread":0.190321308305925,"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."}}