{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004262223,0.0001924461,0.0002633895,0.0001604661,0.0001528546,0.00004910368,0.0002404612,0.0001168313,0.0002767472],"category_scores_gemma":[0.001985031,0.0001753596,0.0001197713,0.0005217814,0.0001806968,0.0001970756,0.00005393515,0.0001424336,0.0006041956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008542633,"about_ca_system_score_gemma":0.00004030976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002101213,"about_ca_topic_score_gemma":0.0001435363,"domain_scores_codex":[0.9985013,0.00003860446,0.0004696121,0.000329004,0.000291246,0.0003702127],"domain_scores_gemma":[0.9984469,0.0003081666,0.00001744616,0.0005796965,0.0004352203,0.0002125482],"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":[0.0001305925,0.0001937493,0.001493169,0.0001310785,0.00006032367,0.000003807905,0.002376612,0.6060413,0.01893764,0.004904308,0.2409263,0.1248011],"study_design_scores_gemma":[0.0001865706,0.0001027017,0.001030084,0.00003970354,0.00004147966,0.000003150763,0.000155109,0.9602513,0.002359399,0.02533947,0.01019137,0.0002996307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1291601,0.00004687514,0.8643402,0.001285597,0.000375957,0.0002006957,0.0000316952,0.0003106745,0.004248201],"genre_scores_gemma":[0.903088,0.00001432806,0.09537311,0.0004405087,0.0007616243,0.00002254571,0.00001102524,0.00002656826,0.0002622987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7739279,"threshold_uncertainty_score":0.7765914,"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."}}