{"id":"W2563665997","doi":"10.5942/jawwa.2017.109.0001","title":"Impact of Urban Development on Energy Use in a Distribution System","year":2016,"lang":"en","type":"article","venue":"American Water Works Association","topic":"Water Systems and Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Kingston Health Sciences Centre","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Lift (data mining); Energy (signal processing); Enhanced Data Rates for GSM Evolution; Energy system; Energy source; Energy distribution; Renewable energy; Computer science; Engineering; Mathematics; Telecommunications; Statistics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003687056,0.000227985,0.0001183139,0.0004852492,0.0004239615,0.0009698024,0.0001791094,0.0001709153,0.001881484],"category_scores_gemma":[0.001616787,0.0001443166,0.000242092,0.0009855194,0.0006994185,0.0005835576,0.0008457208,0.0002024709,0.00009191077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340582,"about_ca_system_score_gemma":0.0005431253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01294675,"about_ca_topic_score_gemma":0.02990204,"domain_scores_codex":[0.9995118,0.0001977273,0.00002487075,0.00004039848,0.00007896178,0.0001461643],"domain_scores_gemma":[0.999345,0.0002384799,0.0001670586,0.00005411784,0.0001258381,0.00006957522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003152407,0.0001805263,0.828965,0.00007667571,0.0001566063,0.0007284182,0.0003989669,0.1264848,0.005269405,0.004827053,0.0004789123,0.03211839],"study_design_scores_gemma":[0.00002191501,0.0004176686,0.923293,0.00003722401,0.0000970286,0.0003525114,0.002929179,0.05933711,0.006525351,0.001867243,0.005088711,0.00003305882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967183,0.00004573289,0.0005181122,0.00004906704,0.000002239515,0.000005301282,0.00005960639,0.000005236048,0.002596336],"genre_scores_gemma":[0.9997212,0.00003353171,0.00008350497,0.000003383167,7.263407e-7,0.000001395932,0.00002178391,0.000001357074,0.0001331676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01294675,"threshold_uncertainty_score":0.02574277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00431119273931165,"score_gpt":0.1770412656792725,"score_spread":0.1727300729399608,"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."}}