{"id":"W4386325141","doi":"10.2166/ws.2023.227","title":"How different regional approaches to the network design result in key differences in burst event severity and failure vulnerability","year":2023,"lang":"en","type":"article","venue":"Water Science & Technology Water Supply","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Intrusion; Flooding (psychology); Environmental science; Flexibility (engineering); Vulnerability (computing); Network planning and design; Key (lock); Pipe network analysis; Computer science; Computer security; Computer network; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.001144429,0.000237036,0.0002815933,0.0005318957,0.0002194798,0.000212347,0.000684329,0.0001790532,0.000002542087],"category_scores_gemma":[0.0000197498,0.0001183386,0.00002434219,0.001215329,0.0004055022,0.0003007364,0.0003704188,0.0003144506,0.00001364521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001113632,"about_ca_system_score_gemma":0.00001179426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005674816,"about_ca_topic_score_gemma":0.001645801,"domain_scores_codex":[0.9979298,0.00009204284,0.0002955467,0.0005586508,0.0002676261,0.0008563716],"domain_scores_gemma":[0.999409,0.00002388785,0.00001670774,0.0004516974,0.00002739035,0.00007134974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005514915,0.00008976377,0.5152595,0.0001225808,0.00002383955,0.00004846781,0.02160796,0.4479061,0.008734408,0.0009430433,0.002253733,0.002955474],"study_design_scores_gemma":[0.00121967,0.000293311,0.3744435,0.0002660649,0.00001705767,0.00007417135,0.002700964,0.4493434,0.1486913,0.01533947,0.006284041,0.001327003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580687,0.00003297856,0.0119276,0.02876507,0.0002587219,0.0006321609,0.000003437974,0.0003011822,0.0000101256],"genre_scores_gemma":[0.9982142,0.00001400069,0.001202147,0.00002592723,0.00004507562,0.000296738,0.00001178289,0.00001488175,0.000175208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.140816,"threshold_uncertainty_score":0.4825708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04499359231412089,"score_gpt":0.2002512247355622,"score_spread":0.1552576324214413,"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."}}