{"id":"W3095896898","doi":"10.4043/30160-ms","title":"Transforming Offshore Oil and Gas Production Platforms into Smart Unmanned Installations","year":2020,"lang":"en","type":"article","venue":"Offshore Technology Conference Asia","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cybernet Systems Corporation (Canada)","funders":"","keywords":"Submarine pipeline; Automation; Crew; SAFER; Robotics; Engineering; Process (computing); Production (economics); Robot; Aeronautics; Marine engineering; Computer science; Artificial intelligence; Computer security; Mechanical engineering; Operating system","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":[0.0001295525,0.0002721001,0.0001089341,0.000262519,0.000247087,0.0003415006,0.0002492449,0.0002749418,0.00174153],"category_scores_gemma":[0.0001959331,0.00008536116,0.0001530528,0.0001438302,0.0003905908,0.0005610668,0.0009740498,0.0001719248,0.0004802723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001453543,"about_ca_system_score_gemma":0.0002641066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007524083,"about_ca_topic_score_gemma":0.001190881,"domain_scores_codex":[0.9998553,0.0000207475,0.000004568256,0.00002646842,0.00005984796,0.00003315713],"domain_scores_gemma":[0.9998946,0.0000135876,0.00002603946,0.0000270179,0.00001477554,0.00002396376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002910126,0.0002562863,0.007203134,0.0004764907,0.00003100311,0.003223613,0.001196303,0.1247531,0.5878999,0.01217329,0.002493775,0.2600021],"study_design_scores_gemma":[0.0001319719,0.004060732,0.04236153,0.000198385,0.00006094703,0.003101727,0.0041353,0.3538206,0.3892877,0.01782574,0.1848702,0.000145149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8428969,0.0001307711,0.1364238,0.0001826575,0.00006133906,0.0002260722,0.0001421133,0.00077535,0.01916107],"genre_scores_gemma":[0.9448383,0.00009173969,0.05028213,0.00002505636,0.00000489174,0.00005643559,0.00007664429,0.00002421348,0.004600575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00174153,"threshold_uncertainty_score":0.005825996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509304146466835,"score_gpt":0.2212301059266748,"score_spread":0.2061370644620065,"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."}}