{"id":"W1244186400","doi":"10.5942/jawwa.2015.107.0122","title":"An Implicit Model for Water Rate Setting Within Municipal Utilities","year":2015,"lang":"en","type":"article","venue":"American Water Works Association","topic":"Water resources management and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Revenue; Non-revenue water; Water utility; Water conservation; Water supply; Water use; Service (business); Environmental economics; Water resources; Economics; Business; Natural resource economics; Finance; Environmental science; Environmental engineering; Economy","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000701553,0.0001692352,0.0001959353,0.00009914094,0.00009385439,0.0002079008,0.0001490535,0.00006682312,0.000005745609],"category_scores_gemma":[0.00001697474,0.0001255694,0.00005086347,0.00008462407,0.00001994914,0.0004841351,0.00003681082,0.0001044545,0.00002257808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002736608,"about_ca_system_score_gemma":0.000003982426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009756679,"about_ca_topic_score_gemma":0.00005302412,"domain_scores_codex":[0.9988555,0.00006106978,0.0002655227,0.0001866565,0.000164146,0.0004671284],"domain_scores_gemma":[0.9995505,0.00002207032,0.00006954034,0.0001849663,0.0000873812,0.00008558465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002208099,0.00001098833,0.001616503,0.00001140295,0.00005567972,2.584053e-7,0.01915874,0.9764457,0.0009997538,0.00001648034,0.0007093579,0.0009530742],"study_design_scores_gemma":[0.0003685146,0.00004885048,0.0001029985,0.000009635897,0.0000390248,1.230058e-7,0.001579014,0.9903714,0.005952165,0.000581387,0.0007254815,0.0002214095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9125791,0.000009107776,0.08570658,0.000268756,0.0001798127,0.000282149,0.000008863964,0.0004048284,0.0005607781],"genre_scores_gemma":[0.9941617,0.000005281664,0.003525578,0.0001679821,0.0001509098,0.00007670341,0.0004397838,0.00005873108,0.001413366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.082181,"threshold_uncertainty_score":0.5120572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01397397277209402,"score_gpt":0.2279111584311855,"score_spread":0.2139371856590915,"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."}}