{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004479085,0.00009938659,0.0002260387,0.00005776967,0.00009186413,0.000008029288,0.0002039254,0.00004003403,0.004617333],"category_scores_gemma":[0.00004115667,0.00008005436,0.0001528976,0.0003186428,0.00005656404,0.00006749127,0.0001063765,0.0003932037,0.000004281223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116864,"about_ca_system_score_gemma":0.00002017686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000216722,"about_ca_topic_score_gemma":0.00003915958,"domain_scores_codex":[0.9990327,0.00007349119,0.0003264803,0.0001555357,0.0002699288,0.0001418844],"domain_scores_gemma":[0.9993972,0.00009301015,0.00002926748,0.0003817999,0.00005434916,0.00004443291],"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":[0.00001065549,0.0001237954,0.00967338,0.000180595,0.00009944716,0.000003661963,0.0002391907,0.9552001,0.0106068,0.005405555,0.01685627,0.001600583],"study_design_scores_gemma":[0.0002500445,0.00007249115,0.04257344,0.000004468121,0.00007067746,0.000003573202,0.0008379291,0.9278418,0.005787157,0.003835174,0.01848018,0.0002430407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9428315,0.00005785757,0.005247487,0.0003369557,0.0003919329,0.0001379762,0.00005558835,0.0002547138,0.05068596],"genre_scores_gemma":[0.9961341,0.0000179347,0.002765392,0.0000552957,0.00002304378,0.00001757733,0.0000240618,0.00000806068,0.0009545508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05330256,"threshold_uncertainty_score":0.9962926,"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."}}