{"id":"W2899861592","doi":"10.1115/ipc2018-78146","title":"Automated Creation of the Pipeline Digital Twin During Construction: Improvement to Construction Quality and Pipeline Integrity","year":2018,"lang":"en","type":"article","venue":"","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"March of Dimes Canada","funders":"National Aeronautics and Space Administration","keywords":"Asset management; Asset (computer security); Pipeline (software); Workflow; Computer science; Pipeline transport; Traceability; Analytics; IT asset management; Engineering; Database; Computer security; Software engineering; 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":[0.0044051,0.0007436976,0.0006271654,0.002651629,0.0007643696,0.002460332,0.001557872,0.000695242,0.004659003],"category_scores_gemma":[0.01775733,0.0005459743,0.0004293672,0.002257229,0.001086728,0.003835787,0.003136493,0.0009735336,0.001445992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001006521,"about_ca_system_score_gemma":0.00239639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002884335,"about_ca_topic_score_gemma":0.004545147,"domain_scores_codex":[0.995152,0.0005922959,0.0002460179,0.0005870642,0.003216588,0.0002060707],"domain_scores_gemma":[0.987475,0.002318568,0.001451027,0.004038737,0.004209217,0.0005075491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007355633,0.0003661208,0.02660494,0.0008027614,0.00004941937,0.0003833687,0.002487314,0.03316426,0.1376885,0.005199399,0.007121414,0.7853971],"study_design_scores_gemma":[0.0001592196,0.003200263,0.08666667,0.0004177348,0.0002087257,0.001678882,0.00336427,0.3407047,0.4287014,0.01020557,0.1242517,0.0004408672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1733788,0.0003541319,0.8101467,0.0004029738,0.0001336073,0.0006804153,0.001054841,0.007095068,0.00675352],"genre_scores_gemma":[0.4138571,0.0002343217,0.5811673,0.00007361623,0.00002850503,0.0002265817,0.001149437,0.0008260915,0.002437023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004659003,"threshold_uncertainty_score":0.02329665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008575476309815,"score_gpt":0.242353753068677,"score_spread":0.2322679983055788,"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."}}