{"id":"W2554757557","doi":"10.1115/ipc2016-64295","title":"Optimized Methods of Recording Pipeline Pressure Fluctuations for Pipeline Integrity Analysis","year":2016,"lang":"en","type":"article","venue":"","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada); University of Alberta","funders":"Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Transportation","keywords":"SCADA; Pipeline (software); Interval (graph theory); Pressure measurement; Computer science; Petroleum engineering; Environmental science; Engineering; Mechanical engineering; Mathematics; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009946628,0.0001658069,0.0004409425,0.0003244734,0.00003379895,0.00001070209,0.0002128842,0.0001053507,0.0002948264],"category_scores_gemma":[0.002129844,0.0001166802,0.0002087407,0.0005804822,0.00004746849,0.0001440213,0.00004457104,0.0001076715,0.000001454873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004526707,"about_ca_system_score_gemma":0.00001647786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007112593,"about_ca_topic_score_gemma":0.00001215133,"domain_scores_codex":[0.9989613,0.00008014599,0.0004548025,0.0002150407,0.00009557894,0.0001931908],"domain_scores_gemma":[0.9977084,0.001429483,0.00008814233,0.0003952069,0.0003245328,0.00005416973],"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":[0.0001345943,0.0001117421,0.004138733,0.0003960855,0.002458934,7.475215e-7,0.0001970827,0.0102971,0.7646033,0.03811541,0.01207968,0.1674665],"study_design_scores_gemma":[0.001011529,0.00005917728,0.0007967813,0.0001042003,0.001821046,0.000001976198,0.00002663284,0.5663945,0.2765959,0.151781,0.0009385342,0.000468741],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001495424,0.00005828419,0.9928256,0.0001552526,0.00009109599,0.0003109868,0.00006987345,0.001008794,0.003984706],"genre_scores_gemma":[0.1415526,0.00002062046,0.8579549,0.000006941481,0.00004892185,0.00006660094,0.00001083706,0.00002962879,0.0003089455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5560974,"threshold_uncertainty_score":0.4758081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03791737428265043,"score_gpt":0.3472374804880714,"score_spread":0.309320106205421,"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."}}