{"id":"W2008409871","doi":"10.4043/23734-ms","title":"Pipeline Engineering Solutions for Harsh Arctic Environments: Technology Challenges and Constraints for Advanced Numerical Simulations","year":2012,"lang":"en","type":"article","venue":"OTC Arctic Technology Conference","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Pipeline transport; Computer science; Pipeline (software); Marine engineering; Submarine pipeline; Arctic; Systems engineering; Engineering; Geology; Mechanical engineering; Oceanography; Geotechnical 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001191248,0.0003189512,0.0003670194,0.0005413521,0.0001368035,0.0000131615,0.000266256,0.0005078275,0.00001401693],"category_scores_gemma":[0.0006918489,0.0003522714,0.00005403719,0.0002444872,0.0003994056,0.0001760804,0.0001237648,0.0003780593,0.000008144622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001051479,"about_ca_system_score_gemma":0.00001426789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.447944e-7,"about_ca_topic_score_gemma":0.000002118216,"domain_scores_codex":[0.9984019,0.000004692221,0.0003007449,0.0003294183,0.00007634164,0.0008869217],"domain_scores_gemma":[0.9991348,0.0002559008,0.00005053388,0.0004173191,0.00005340421,0.00008800587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001750805,0.0001855664,0.001816652,0.0006629628,0.00028448,0.000002485314,0.0002633153,0.01733463,0.0264205,0.5174201,0.00007817864,0.4355137],"study_design_scores_gemma":[0.005541881,0.000926454,0.003913445,0.0008793136,0.0005543184,0.0004014514,0.003300995,0.7645818,0.03901304,0.07799824,0.0995004,0.003388671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03519884,0.008695614,0.9493176,0.002487408,0.0004427235,0.0008498544,0.00007906994,0.002852337,0.00007651572],"genre_scores_gemma":[0.9485723,0.0007394158,0.04992219,0.00000840511,0.00004645852,0.0005968249,0.00001730771,0.00006111414,0.00003591705],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9133735,"threshold_uncertainty_score":0.999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02425417309110608,"score_gpt":0.2296845607742602,"score_spread":0.2054303876831541,"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."}}