{"id":"W1980069936","doi":"10.1115/1.1854706","title":"Risk Analysis of Running a Deep-Water Production Test From a Dynamically Positioned Vessel in the North Atlantic","year":2005,"lang":"en","type":"article","venue":"Journal of Offshore Mechanics and Arctic Engineering","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada); University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Disconnection; Production (economics); Risk analysis (engineering); Computer science; Focus (optics); Risk assessment; Environmental science; Submarine pipeline; Marine engineering; Reliability engineering; Operations research; Engineering; Business; Geology; Computer security; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.002108502,0.0001117074,0.0004381973,0.0007374012,0.00007040193,0.00008320234,0.00030149,0.00003741021,0.00002241122],"category_scores_gemma":[0.0009457688,0.0000615655,0.0002344678,0.001237907,0.00001018196,0.0002235292,0.00003754809,0.0002769376,0.000001267532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003368779,"about_ca_system_score_gemma":0.00001300575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006209669,"about_ca_topic_score_gemma":0.0004118682,"domain_scores_codex":[0.9980444,0.00006904792,0.00086461,0.0001764851,0.000694641,0.0001507894],"domain_scores_gemma":[0.9985551,0.0005470054,0.0003711439,0.0002277264,0.0002419491,0.00005710622],"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":[0.00005653965,0.00016947,0.1963098,0.00001008053,0.0008205918,0.00003343353,0.004179827,0.7855314,0.00591943,0.0003694612,0.000008865251,0.006591033],"study_design_scores_gemma":[0.0001793111,0.00006659652,0.1327698,0.00003868962,0.0009127022,0.0000301981,0.0005907909,0.8627827,0.0001595607,0.002322398,0.00005881171,0.00008846344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9191517,0.00020576,0.07934596,0.001176737,0.00006727796,0.0000422536,0.000004358043,0.000002929762,0.000003068639],"genre_scores_gemma":[0.9934489,0.0004637299,0.005947005,0.00002293653,0.0001024986,0.000001001604,0.000004766804,0.000005958848,0.000003260915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07725129,"threshold_uncertainty_score":0.2510568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01277575744596214,"score_gpt":0.2486499616416961,"score_spread":0.235874204195734,"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."}}