{"id":"W4379033730","doi":"10.1109/tim.2023.3279910","title":"Data Modeling Techniques for Pipeline Integrity Assessment: A State-of-the-Art Survey","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Research Council Canada","keywords":"Pipeline (software); Integrity management; Pipeline transport; Reliability engineering; Computer science; Data integrity; Data modeling; Engineering; Process (computing); Systems engineering; Risk analysis (engineering); Computer security; Software engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007959717,0.002108809,0.002159948,0.01026157,0.0008352335,0.00533757,0.003945742,0.00221322,0.003601472],"category_scores_gemma":[0.02050727,0.001333874,0.003513949,0.01381603,0.001417019,0.00930104,0.002152544,0.002600624,0.001979786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001721581,"about_ca_system_score_gemma":0.004428323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008286365,"about_ca_topic_score_gemma":0.004144331,"domain_scores_codex":[0.9937621,0.001332345,0.001043837,0.0009055125,0.002769468,0.0001867787],"domain_scores_gemma":[0.9742622,0.01793695,0.001435068,0.001575785,0.004551036,0.0002390349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008556307,0.0001404645,0.00380425,0.01939354,0.0003130969,0.0002559396,0.0006002591,0.01558009,0.002065473,0.03383057,0.0152543,0.9086765],"study_design_scores_gemma":[0.00002668026,0.0002200692,0.004249483,0.02134714,0.0008397135,0.001374056,0.00135343,0.05173953,0.006486693,0.0391819,0.872848,0.0003332717],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004848561,0.736414,0.2388155,0.003395763,0.0007778133,0.0003303974,0.001589516,0.001066159,0.01276224],"genre_scores_gemma":[0.03192766,0.8616343,0.09915008,0.0008554928,0.0005696836,0.0003093645,0.003173093,0.0002554645,0.002124792],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01026157,"threshold_uncertainty_score":0.04209554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1317487025558981,"score_gpt":0.3296049731064006,"score_spread":0.1978562705505025,"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."}}