{"id":"W3203455084","doi":"10.2166/wpt.2021.094","title":"A review of water quality factors in water main failure prediction models","year":2021,"lang":"en","type":"review","venue":"Water Practice & Technology","topic":"Water Systems and Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Water quality; Quality (philosophy); Predictive modelling; Identification (biology); Process (computing); Set (abstract data type); Environmental science; Computer science; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001255199,0.0006004227,0.002403262,0.0006890432,0.00004032758,0.00004126106,0.000415678,0.001261533,0.0001305997],"category_scores_gemma":[0.00009482972,0.0003224641,0.0003152939,0.0003544466,0.0000557844,0.0006970923,0.0002627108,0.001004362,0.00007929622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003011492,"about_ca_system_score_gemma":0.00003598944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009947622,"about_ca_topic_score_gemma":0.00007872723,"domain_scores_codex":[0.9961542,0.0005080812,0.001850855,0.0005730902,0.0002497947,0.000663955],"domain_scores_gemma":[0.9985723,0.00006087056,0.0001893742,0.0009475822,0.0001778085,0.00005202978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001650586,0.0004593952,0.00002112996,0.8833421,0.002036491,0.0003057713,0.003981449,0.01206122,0.0007410908,0.0009606909,0.01049549,0.08557864],"study_design_scores_gemma":[0.0001427429,0.00003017642,5.663306e-8,0.03668783,0.0004829667,0.0001664187,0.0001086314,0.0001565628,0.003108645,0.00009984125,0.9586053,0.0004108048],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004387784,0.9936873,0.003134052,0.000509895,0.0005080496,0.001172385,0.0000570064,0.0004248595,0.000462567],"genre_scores_gemma":[0.0006338984,0.9966345,0.0006334995,0.00003612849,0.00006012698,0.0003244306,0.00132038,0.0001258596,0.0002312117],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9481099,"threshold_uncertainty_score":0.9999228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03719746393817485,"score_gpt":0.2973692493129634,"score_spread":0.2601717853747886,"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."}}