{"id":"W1986216716","doi":"10.1115/omae2009-79439","title":"Numerical Simulations of Wrinkle Sleeve Repair on Norman Wells: Zama Pipeline","year":2009,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Wrinkle; Pipeline (software); Curvature; Pipeline transport; Structural engineering; Finite element method; Engineering; Computer simulation; Mechanical engineering; Simulation; Materials science; Geometry","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":[0.0004205059,0.0004318389,0.0006375104,0.0006778112,0.0008080901,0.0008826258,0.0008401481,0.001822327,0.002546307],"category_scores_gemma":[0.001797865,0.0003618294,0.000487819,0.0006926572,0.001097059,0.0003648289,0.0004885321,0.0006011102,0.0002550412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001659388,"about_ca_system_score_gemma":0.001536167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06521643,"about_ca_topic_score_gemma":0.05225746,"domain_scores_codex":[0.9997661,0.00003845801,0.00001130031,0.00002999426,0.00007337338,0.00008081863],"domain_scores_gemma":[0.9990823,0.0005089474,0.000107937,0.00004481123,0.0001751078,0.00008087975],"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":[0.00006626753,0.0000506064,0.002170973,0.00002615891,0.000006946561,0.0001283546,0.0001035172,0.993652,0.001634182,0.0005514707,0.0002261965,0.001383461],"study_design_scores_gemma":[0.00001496826,0.00006434637,0.001729723,0.00000920187,0.000005310125,0.0000191857,0.0001754833,0.9962837,0.001044879,0.0001368455,0.0005064192,0.000009891569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818957,0.0001322778,0.006371967,0.000185287,0.0000357978,0.00005236781,0.0004212796,0.0001522293,0.01075303],"genre_scores_gemma":[0.9927181,0.00006665447,0.003683804,0.00002259706,0.000002957189,0.0000443788,0.0001976422,0.00002358609,0.003240139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06521643,"threshold_uncertainty_score":0.1296737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009783964089074493,"score_gpt":0.2397370775974298,"score_spread":0.2299531135083553,"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."}}