{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009430951,0.0001211344,0.0001452483,0.00008081795,0.00005327807,0.00003372052,0.00008537119,0.00008584833,0.00001708227],"category_scores_gemma":[0.0001364184,0.00009076681,0.00002974026,0.0002331494,0.0001870308,0.0001145415,0.00006926147,0.0001291384,0.000004224155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000510709,"about_ca_system_score_gemma":0.000007978893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003037856,"about_ca_topic_score_gemma":0.00001543271,"domain_scores_codex":[0.9993189,0.00000634261,0.0002990857,0.0001352367,0.0001109005,0.0001295184],"domain_scores_gemma":[0.9995915,0.00002130866,0.00003699801,0.000220188,0.00009535335,0.00003461963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001023661,0.0001303452,0.07348818,0.0009243842,0.0002422752,0.0000018424,0.0009102963,0.009556736,0.3707708,0.01818879,0.003974312,0.5217096],"study_design_scores_gemma":[0.0006541351,0.000106016,0.06709261,0.0001081239,0.00002281218,0.00004698458,0.001024421,0.09885912,0.830053,0.0006440001,0.001046601,0.0003422108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9638483,0.00001791643,0.03199489,0.0002944175,0.0004626072,0.0001549989,0.00002230944,0.001704687,0.001499857],"genre_scores_gemma":[0.9940869,0.000007451586,0.005718201,0.000008679644,0.00008055305,0.000006422883,0.000003446217,0.00001103146,0.0000772834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5213674,"threshold_uncertainty_score":0.3701363,"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."}}