{"id":"W3084382166","doi":"","title":"Optimisation of Ultra-Deepwater Pipeline Design, Construction and Pre-Commissioning","year":2020,"lang":"en","type":"article","venue":"The 30th International Ocean and Polar Engineering Conference","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Intecsea (Canada)","funders":"","keywords":"Pipeline (software); Project commissioning; Engineering; Marine engineering; Forensic engineering; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102111,0.0007975112,0.0007832763,0.0006899117,0.0006132094,0.001476747,0.0007681915,0.00082577,0.004436363],"category_scores_gemma":[0.002280648,0.00056835,0.000502845,0.0006700445,0.0003901852,0.001073591,0.0008092977,0.000810884,0.001104469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001399878,"about_ca_system_score_gemma":0.002193132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005827552,"about_ca_topic_score_gemma":0.009440288,"domain_scores_codex":[0.999263,0.0001397615,0.00003306652,0.0001043285,0.00030465,0.000155224],"domain_scores_gemma":[0.9989229,0.0003972919,0.0001342988,0.0001153461,0.0003488306,0.0000813575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007505499,0.0002400382,0.00357571,0.0004795243,0.00003113563,0.0001617738,0.0001519361,0.691539,0.1336856,0.001683913,0.002343284,0.1653576],"study_design_scores_gemma":[0.0001060949,0.0024869,0.0146609,0.0000667595,0.00009101372,0.0001683357,0.0003798442,0.8092845,0.1528589,0.002906196,0.01690556,0.00008502883],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4658119,0.0008770171,0.5125108,0.000545228,0.0001532969,0.000318416,0.0005927201,0.002266424,0.01692405],"genre_scores_gemma":[0.9395518,0.0001963102,0.0543517,0.00003662816,0.00001069556,0.00009339307,0.0002989958,0.0001950338,0.005265481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005827552,"threshold_uncertainty_score":0.01484114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536822633892232,"score_gpt":0.1950870738527787,"score_spread":0.1797188475138563,"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."}}