{"id":"W4415777405","doi":"10.2118/229302-ms","title":"Digital Twin for Pipeline Leak Monitoring","year":2025,"lang":"","type":"article","venue":"","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Birds Canada; Memorial University of Newfoundland","funders":"","keywords":"Pipeline (software); Leak; Context (archaeology); Pipeline transport; Situation awareness; Leak detection; Interactive visual analysis; Visualization","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":[0.001231479,0.0006816478,0.0005474646,0.001250124,0.0003704371,0.001959432,0.001501009,0.0006819561,0.01422775],"category_scores_gemma":[0.004195662,0.0004934782,0.0006017186,0.0007778462,0.0007682812,0.003059725,0.003724997,0.0009517138,0.001889651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009870708,"about_ca_system_score_gemma":0.000858863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003541245,"about_ca_topic_score_gemma":0.002635256,"domain_scores_codex":[0.9990112,0.0001706656,0.00005877118,0.0002303956,0.0004671648,0.00006186269],"domain_scores_gemma":[0.9982015,0.0003864136,0.0001405672,0.0006992877,0.0004081004,0.0001640891],"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":[0.003161863,0.0004731704,0.01933576,0.0005698539,0.000197342,0.0007997024,0.001294763,0.2754182,0.148662,0.05000447,0.02956544,0.4705173],"study_design_scores_gemma":[0.00006013213,0.0002871177,0.001901545,0.00003487417,0.00003343683,0.0001599617,0.0001012022,0.9274043,0.03591671,0.01067068,0.02337005,0.00005983444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05707724,0.00008579226,0.8989223,0.0002775558,0.00014562,0.0002094003,0.0009455082,0.0312863,0.01105035],"genre_scores_gemma":[0.6827948,0.0001251691,0.3034152,0.0001994968,0.00004049759,0.0001929968,0.001691594,0.00184659,0.009693656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01422775,"threshold_uncertainty_score":0.04759657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081687826593259,"score_gpt":0.2623469126855395,"score_spread":0.2415300344196069,"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."}}