{"id":"W3191712575","doi":"10.1061/9780784483602.002","title":"ATCO’s Urban Pipeline Replacement (UPR) Program","year":2021,"lang":"en","type":"article","venue":"Pipelines 2021","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ATCO (Canada); Alberta Energy","funders":"","keywords":"Pipeline (software); Computer science; Programming language","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":[0.000117866,0.0001734192,0.000207346,0.00004668607,0.00004524295,0.00009190066,0.00009001565,0.0000809416,0.0005403882],"category_scores_gemma":[0.00003770677,0.0001672497,0.00007699018,0.0002923741,0.00001079549,0.0001033444,0.00004672839,0.0001013717,0.0002108332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004697605,"about_ca_system_score_gemma":0.00002640004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001639965,"about_ca_topic_score_gemma":0.0001491485,"domain_scores_codex":[0.9989114,0.00002837688,0.0003658272,0.0002514404,0.0001794167,0.0002635763],"domain_scores_gemma":[0.9993205,0.00001453536,0.00003110441,0.0003738598,0.0001732003,0.00008679862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000234245,0.0002781494,0.007050368,0.0004626555,0.0001198149,0.000148825,0.0007656028,0.113461,0.002886261,0.0003160316,0.820551,0.05393688],"study_design_scores_gemma":[0.0005600488,0.000031452,0.0003057909,0.00008606126,0.00003133508,0.0000383605,0.0001601713,0.3219454,0.008864937,0.00002672059,0.6676095,0.0003402495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09782971,0.02709864,0.6536078,0.003870981,0.01888995,0.003196141,0.0001618555,0.005355482,0.1899895],"genre_scores_gemma":[0.8703804,0.0007634382,0.03526372,0.0002426004,0.004085261,0.0002920836,0.0008389314,0.0001842137,0.08794937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7725506,"threshold_uncertainty_score":0.6820246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009361435412575185,"score_gpt":0.2203585966839798,"score_spread":0.2109971612714046,"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."}}