{"id":"W4300622768","doi":"10.5957/icetech-2008-174","title":"Probabilistic Pipeline Burial Analysis for Protection against Ice Scour","year":2008,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Seabed; Iceberg; Probabilistic logic; Keel; Pipeline (software); Geology; Range (aeronautics); Stress (linguistics); Probabilistic analysis of algorithms; Reliability (semiconductor); Marine engineering; Pipeline transport; Geotechnical engineering; Engineering; Oceanography; Sea ice; Statistics; Aerospace engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001415253,0.0001480096,0.0002891403,0.0002021223,0.0001495747,0.00002156798,0.0001080007,0.0001334952,0.0001559889],"category_scores_gemma":[0.0001907455,0.0001167658,0.0003632313,0.000833498,0.00006071189,0.0001031256,0.00001065353,0.0001637624,0.00001996757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000858062,"about_ca_system_score_gemma":0.00001503369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002001063,"about_ca_topic_score_gemma":0.0004903995,"domain_scores_codex":[0.9991149,0.00001950537,0.0002972386,0.0002187702,0.0001477956,0.0002017778],"domain_scores_gemma":[0.9994742,0.00005904662,0.00002742119,0.0002243555,0.0001503857,0.00006455422],"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":[0.00004773386,0.00004194612,0.0002141313,0.0001638146,0.0009881831,0.000002554642,0.0002836421,0.9889032,0.004403312,0.0003088706,0.001555816,0.003086828],"study_design_scores_gemma":[0.0002917852,0.00003089983,0.0008289878,0.000006167437,0.0005219927,0.000004463703,0.00007885463,0.990835,0.004735502,0.0006209113,0.001819002,0.0002264347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6784644,0.00005467615,0.3172784,0.000254214,0.0003208111,0.0005951338,0.00002179938,0.0004726887,0.0025379],"genre_scores_gemma":[0.9962776,0.00003783762,0.002196712,0.00003523336,0.0002941834,0.00008805241,0.00004365901,0.00001378896,0.001012982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3178131,"threshold_uncertainty_score":0.4761573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02603034442896133,"score_gpt":0.2328509843842563,"score_spread":0.206820639955295,"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."}}