{"id":"W2735691628","doi":"10.5006/c2017-09648","title":"Correlation of Inline and Aboveground Integrity Inspection Data for Comprehensive Pipeline Integrity Management Program","year":2017,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petroleum Technology Alliance Canada","funders":"","keywords":"Integrity management; Data integrity; Pipeline (software); Structural integrity; Reliability engineering; Computer science; Personal Integrity; Forensic engineering; Environmental science; Engineering; Computer security; Structural 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":[0.003466735,0.0004787529,0.0005538698,0.005068717,0.0003379939,0.00120642,0.0005279404,0.0004483878,0.001768805],"category_scores_gemma":[0.01002705,0.0002054985,0.0003205555,0.004659276,0.0001765484,0.000965193,0.0009965892,0.0004709746,0.0006446314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009806911,"about_ca_system_score_gemma":0.001775443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00860207,"about_ca_topic_score_gemma":0.01584516,"domain_scores_codex":[0.9956665,0.0008462881,0.0004650389,0.0005918981,0.002099173,0.0003311044],"domain_scores_gemma":[0.9806406,0.002827357,0.004066361,0.001836219,0.01001325,0.0006161336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002572307,0.0004353875,0.8369365,0.0002150036,0.0001221159,0.0002601375,0.0004023928,0.0227586,0.01328454,0.0006928403,0.005019859,0.1196154],"study_design_scores_gemma":[0.00002339745,0.0007971347,0.8157703,0.0001429969,0.0001180576,0.0004681816,0.001195342,0.1415118,0.02866367,0.0005790784,0.01066146,0.00006857495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956124,0.000288408,0.07830667,0.0001948552,0.00004767641,0.0007435412,0.01241611,0.002561514,0.009828841],"genre_scores_gemma":[0.9511504,0.0001105975,0.03811096,0.00002937996,0.00001111691,0.0001478447,0.008889129,0.00004978357,0.001500848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00860207,"threshold_uncertainty_score":0.01833409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04683459555110497,"score_gpt":0.3075196147274612,"score_spread":0.2606850191763562,"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."}}