{"id":"W2109197612","doi":"10.1115/ipc2006-10150","title":"Deepwater Pipelines: Reliability of Finite Element Models in the Prediction of Collapse and Collapse Propagation Loads","year":2006,"lang":"en","type":"article","venue":"Volume 1: Project Management; Design and Construction; Environmental Issues; GIS/Database Development; Innovative Projects and Emerging Issues; Operations and Maintenance; Pipelining in Northern Environments; Standards and Regulations","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Buckle; Finite element method; Structural engineering; Pipeline transport; Engineering; Residual; Eccentricity (behavior); Bending; Computer science; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002789241,0.001160714,0.0008257574,0.00107627,0.0004199519,0.001153813,0.001080436,0.001814084,0.001351461],"category_scores_gemma":[0.01050554,0.000896809,0.0007960935,0.0008100133,0.0009750736,0.001596075,0.0009530658,0.001332886,0.0007092631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007526141,"about_ca_system_score_gemma":0.0006950701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009738352,"about_ca_topic_score_gemma":0.005028717,"domain_scores_codex":[0.9986499,0.0005730282,0.000098592,0.000158101,0.0004599904,0.00006041771],"domain_scores_gemma":[0.9913704,0.005904358,0.0007836915,0.0007372422,0.001094407,0.0001098932],"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":[0.0001198103,0.00006758513,0.004921807,0.0001365731,0.00004310056,0.00005553488,0.0001163091,0.9634632,0.00563638,0.001869285,0.0004014655,0.023169],"study_design_scores_gemma":[0.000002993713,0.00003947741,0.0005529681,0.00002698809,0.000007655308,0.0000124575,0.00001501071,0.9960065,0.002349225,0.0005702534,0.0004039589,0.00001254578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2597789,0.006084477,0.7234457,0.0008802972,0.0001573359,0.0001402198,0.0008342083,0.001646411,0.007032357],"genre_scores_gemma":[0.9360422,0.001819279,0.05930292,0.00007865451,0.00005047512,0.0001081596,0.0004619308,0.0003056067,0.001830731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009738352,"threshold_uncertainty_score":0.01936334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146838081975909,"score_gpt":0.2236302460357864,"score_spread":0.2121618652160273,"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."}}