{"id":"W2331212241","doi":"10.1061/40994(321)59","title":"Integration of Geographic Information System and Probabilistic Analysis for Optimized Pipe Infrastructure Decisions","year":2008,"lang":"en","type":"article","venue":"","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Geographic information system; Scheduling (production processes); Computer science; Pipeline transport; Pipeline (software); Information system; Service (business); Operations research; Unit (ring theory); Engineering; Operations management; Business; Environmental engineering; Geography","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":[0.002706126,0.0007373098,0.0009977377,0.002861567,0.0005841648,0.002036751,0.0007821665,0.000735104,0.003647713],"category_scores_gemma":[0.007708205,0.0008502703,0.0007705322,0.002828152,0.0004789805,0.002112564,0.001036406,0.0006066212,0.0004311929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002077748,"about_ca_system_score_gemma":0.002849506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02901438,"about_ca_topic_score_gemma":0.03435054,"domain_scores_codex":[0.9985251,0.0006288174,0.0001062614,0.0001384337,0.0005102562,0.00009106503],"domain_scores_gemma":[0.9972249,0.001650168,0.0002715304,0.0001795292,0.000626269,0.00004757391],"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":[0.00004111628,0.00003321398,0.00128404,0.00003350015,0.00003596864,0.0000387844,0.00002650828,0.9514201,0.0003103106,0.01004452,0.0006487981,0.03608312],"study_design_scores_gemma":[0.000005155549,0.00001202826,0.0003842666,0.000004161353,0.00001201648,0.000008150549,0.00001028782,0.9950731,0.0001834168,0.003712689,0.0005862343,0.00000844681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03347243,0.0001865018,0.9569389,0.0003705263,0.00002875345,0.0001630724,0.0004372027,0.001178197,0.007224345],"genre_scores_gemma":[0.6074175,0.0003260162,0.3893763,0.00006881765,0.00004051499,0.0002182164,0.0006777409,0.0001856327,0.001689148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02901438,"threshold_uncertainty_score":0.05769098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008817036883485486,"score_gpt":0.1849550728455162,"score_spread":0.1761380359620307,"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."}}