{"id":"W4312392321","doi":"10.1115/ipc2022-87319","title":"Assessing Geohazard Probability of Pipeline Failure: Lessons and Improvements From the Last 10 Years","year":2022,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BGC Engineering (Canada)","funders":"","keywords":"Geohazard; Integrity management; Pipeline transport; Pipeline (software); Computer science; Risk analysis (engineering); Forensic engineering; Engineering; Reliability engineering; Geotechnical engineering; Business","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":[0.01828873,0.001789051,0.001284325,0.00345778,0.0006100545,0.003554067,0.003131617,0.002023006,0.001597547],"category_scores_gemma":[0.03934421,0.0006331137,0.001244635,0.00296038,0.00144971,0.004259782,0.001838678,0.00253189,0.0007356906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002801561,"about_ca_system_score_gemma":0.003920573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06076717,"about_ca_topic_score_gemma":0.04105958,"domain_scores_codex":[0.9960293,0.001081451,0.0004198169,0.0007844146,0.001498055,0.0001869283],"domain_scores_gemma":[0.9623145,0.009259986,0.002826447,0.002745044,0.02130729,0.00154678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001613548,0.0003756041,0.1331545,0.0007658793,0.0002963892,0.0001961493,0.0007427266,0.1054115,0.002379849,0.006074984,0.01019721,0.7402439],"study_design_scores_gemma":[0.00007617116,0.002470998,0.2338014,0.002832985,0.0005827686,0.001352116,0.002683567,0.5753833,0.01880376,0.026882,0.1344958,0.000635084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3956701,0.06277115,0.4653473,0.03819435,0.001803163,0.0004090758,0.003627224,0.00339396,0.02878383],"genre_scores_gemma":[0.7191892,0.0214664,0.2518708,0.001159109,0.0005624621,0.00009272217,0.002352464,0.0004084665,0.002898444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06076717,"threshold_uncertainty_score":0.120827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290317497225372,"score_gpt":0.2260542576033327,"score_spread":0.213151082631079,"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."}}