{"id":"W2316046757","doi":"10.1061/41036(342)36","title":"Application of Optimization Technology to Water Distribution System Master Planning","year":2009,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2009","topic":"Water Systems and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; St. Michael's Hospital","funders":"University of Exeter","keywords":"Variety (cybernetics); Computer science; Reliability (semiconductor); Plan (archaeology); Process (computing); Iterative and incremental development; Optimization problem; Mathematical optimization; Algorithm","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":[0.00006216147,0.0001494012,0.0001711219,0.0001501374,0.00006523066,0.00003272955,0.00009004181,0.00007075865,0.00001632745],"category_scores_gemma":[2.737449e-7,0.0001033132,0.00002158633,0.00006454756,0.0000328878,0.0001024019,0.00003933517,0.00005878602,0.00002804602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005785668,"about_ca_system_score_gemma":2.493587e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003892302,"about_ca_topic_score_gemma":0.000001850588,"domain_scores_codex":[0.9992086,0.00001328827,0.0002618739,0.0001835753,0.0001137084,0.0002189122],"domain_scores_gemma":[0.9997589,0.000002245561,0.00002483961,0.0001508018,0.000005060125,0.00005815436],"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":[0.000026377,0.00002114713,0.006086408,0.00006212491,0.00001742336,0.000003704341,0.0008026774,0.9669879,0.02270314,0.00004002031,0.000213579,0.003035463],"study_design_scores_gemma":[0.001159899,0.0002448577,0.009432707,0.0002971787,0.00007293872,0.00005220638,0.0005583294,0.5003483,0.4156019,0.00007560745,0.07133909,0.0008170586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8935835,0.000300367,0.1039323,0.000280398,0.0001413595,0.0004762568,0.00003915161,0.000244457,0.001002183],"genre_scores_gemma":[0.9985922,0.000005632628,0.0004351149,0.00002147477,0.000042234,0.00002347516,0.0002179391,0.00001570681,0.0006462085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4666397,"threshold_uncertainty_score":0.421299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003407901377645831,"score_gpt":0.1665837971221244,"score_spread":0.1631758957444785,"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."}}