{"id":"W4313149424","doi":"10.1115/ipc2022-87232","title":"Reliability Assessment of Pipeline Third Party Damage","year":2022,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Pipeline transport; Pipeline (software); Reliability (semiconductor); Fault tree analysis; Excavator; Excavation; Environmental science; Population; Engineering; Reliability engineering; Forensic engineering; Computer science; Structural engineering; Geotechnical engineering; Marine engineering; Environmental engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002102079,0.0007617972,0.0006586208,0.002044714,0.0002778441,0.0006104143,0.0009321234,0.0005821696,0.001438854],"category_scores_gemma":[0.006440329,0.000364981,0.001099439,0.00087827,0.0003522804,0.0007592559,0.0006354298,0.0005963561,0.000396519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001412227,"about_ca_system_score_gemma":0.0007330316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01256799,"about_ca_topic_score_gemma":0.005845578,"domain_scores_codex":[0.9985661,0.0004173977,0.00006230395,0.0001817554,0.0006488853,0.0001237069],"domain_scores_gemma":[0.9944869,0.002230204,0.0005730249,0.0005845184,0.001995188,0.0001301622],"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":[0.0001157303,0.00003689959,0.01476824,0.00008186151,0.00007210713,0.0001236006,0.00006850686,0.9613401,0.003454307,0.0007494342,0.0006026828,0.01858642],"study_design_scores_gemma":[0.000004755144,0.0001758746,0.006921753,0.00001291084,0.0000285897,0.0000546431,0.00002762265,0.9902794,0.001476362,0.0006500767,0.0003499683,0.00001816007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7763482,0.001238942,0.2127149,0.0003211077,0.00006782739,0.0001653979,0.001536455,0.0009065135,0.00670063],"genre_scores_gemma":[0.9960182,0.00009165332,0.002984504,0.000008375032,0.00000534745,0.00002318192,0.000300546,0.00002051993,0.0005475817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01256799,"threshold_uncertainty_score":0.02498966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146283069675065,"score_gpt":0.2573352992512731,"score_spread":0.2458724685545224,"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."}}