{"id":"W2999250775","doi":"10.1061/9780784481653.009","title":"Criticality Model to Prioritize Pipeline Rehabilitation Decisions","year":2018,"lang":"en","type":"article","venue":"Pipelines 2018","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Criticality; Pipeline transport; Pipeline (software); Prioritization; Computer science; Failure mode, effects, and criticality analysis; Civil engineering; Engineering; Risk analysis (engineering); Business; Environmental engineering; Management science","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":[0.003680232,0.001698296,0.0009676178,0.002743044,0.0009597167,0.001760616,0.001501535,0.001226439,0.005750146],"category_scores_gemma":[0.009002795,0.0006044236,0.001043854,0.00136987,0.001096469,0.002289246,0.001188278,0.001715552,0.000327494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004087901,"about_ca_system_score_gemma":0.003564915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0118256,"about_ca_topic_score_gemma":0.007672538,"domain_scores_codex":[0.9978071,0.001017664,0.00008124067,0.0003251806,0.0004502861,0.0003184789],"domain_scores_gemma":[0.9943871,0.003978595,0.0005285263,0.00006815277,0.0008218791,0.0002157029],"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":[0.00005858039,0.0000577483,0.001353179,0.00005417615,0.00004632592,0.0001277645,0.0001190725,0.9680896,0.0004446515,0.022079,0.0005609446,0.007008886],"study_design_scores_gemma":[0.0000098673,0.00004071681,0.0001911179,0.000008177901,0.00001580462,0.00001965859,0.0000584249,0.9878672,0.0001333814,0.01119174,0.0004574774,0.000006464441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08486884,0.0002258234,0.8986131,0.0009693332,0.00008526302,0.000525315,0.0002963804,0.0002252422,0.01419072],"genre_scores_gemma":[0.8992438,0.0004105779,0.09326196,0.0001193267,0.00007693884,0.0006034937,0.0002533901,0.00004875098,0.005981686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0118256,"threshold_uncertainty_score":0.02965987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013541233634648,"score_gpt":0.2951419146294458,"score_spread":0.2750065022930993,"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."}}