{"id":"W4413135713","doi":"10.1061/9780784486382.003","title":"Data-Powered Strategies: Enhancing Pipeline Management for Small Water Systems","year":2025,"lang":"en","type":"article","venue":"","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Crop Industry Development Fund","funders":"","keywords":"Pipeline (software); Computer science; Systems engineering; Engineering; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006627139,0.001120181,0.0003879357,0.002288671,0.001165141,0.004717395,0.002768839,0.001040346,0.004000368],"category_scores_gemma":[0.02064836,0.0003435207,0.0003851448,0.001886642,0.001407995,0.006094985,0.003466491,0.0009519528,0.000677294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003366605,"about_ca_system_score_gemma":0.01003575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02481146,"about_ca_topic_score_gemma":0.03572157,"domain_scores_codex":[0.9969679,0.001438662,0.0001401873,0.0002206228,0.001007204,0.0002254383],"domain_scores_gemma":[0.9911876,0.003582165,0.0009131843,0.0009991023,0.002679905,0.0006380022],"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":[0.0002589835,0.0009172021,0.01693718,0.001244634,0.00009230016,0.0004793663,0.003022702,0.215805,0.007192418,0.07599621,0.01374385,0.6643101],"study_design_scores_gemma":[0.0002075326,0.001245621,0.01117724,0.001212593,0.0001309834,0.0003312696,0.01353803,0.6444874,0.02184496,0.1692323,0.1363787,0.0002133869],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1729494,0.001503309,0.7375844,0.01943844,0.0001264269,0.002316332,0.0009557579,0.003571863,0.06155414],"genre_scores_gemma":[0.7770292,0.001053497,0.2157093,0.0003768082,0.00002817903,0.0004095681,0.0006396161,0.0001478695,0.004605985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02481146,"threshold_uncertainty_score":0.04933405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01960341412009809,"score_gpt":0.2312650488489956,"score_spread":0.2116616347288975,"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."}}