{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004278619,0.001816619,0.002407031,0.007201782,0.0003145894,0.00168854,0.001433197,0.001062017,0.002934348],"category_scores_gemma":[0.01090038,0.0008547694,0.003010944,0.009023489,0.0003966421,0.002180821,0.0006219652,0.000857613,0.0006533615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580106,"about_ca_system_score_gemma":0.004592645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007136516,"about_ca_topic_score_gemma":0.008540878,"domain_scores_codex":[0.9982198,0.0005402452,0.0004111039,0.0002525827,0.0005056544,0.00007066316],"domain_scores_gemma":[0.9899923,0.007298954,0.0009905885,0.0001271501,0.001500207,0.00009073067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001346537,0.0001216236,0.001531461,0.3135257,0.001664703,0.0002373785,0.0002573011,0.004980304,0.000705248,0.005092356,0.01508873,0.6566606],"study_design_scores_gemma":[0.00006971895,0.0008140301,0.01169777,0.3171414,0.01261034,0.001032112,0.0005318741,0.005432664,0.001990649,0.006782081,0.6417038,0.0001936506],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003977721,0.9982735,0.0005936599,0.0001656088,0.00009419356,0.00001785506,0.00007157979,0.000006551186,0.0003792901],"genre_scores_gemma":[0.003593769,0.9953063,0.0006849539,0.00008267627,0.00007951749,0.00002188964,0.00007852605,0.000002746202,0.0001496547],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007201782,"threshold_uncertainty_score":0.02262777,"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."}}