{"id":"W2008577916","doi":"10.1115/ipc2004-0057","title":"Quantitative Evaluation of Indirect Inspection Reliability and Pipeline Reliability Based on Statistical Methods","year":2004,"lang":"en","type":"article","venue":"2004 International Pipeline Conference, Volumes 1, 2, and 3","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Manitoba Hydro; Dynamic Systems Analysis (Canada)","funders":"","keywords":"Reliability (semiconductor); Reliability engineering; Pipeline (software); Corrosion; Interval (graph theory); Consistency (knowledge bases); Computer science; Pipeline transport; Forensic engineering; Engineering; Materials science; Mathematics; Artificial intelligence","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":[0.04351008,0.001253676,0.0009699825,0.008870672,0.0005077571,0.002116727,0.001326384,0.0007485581,0.002304801],"category_scores_gemma":[0.1327776,0.0004535537,0.001555616,0.007212034,0.002170522,0.00168038,0.001800665,0.001277203,0.0004999888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008583987,"about_ca_system_score_gemma":0.00113602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001308275,"about_ca_topic_score_gemma":0.001491578,"domain_scores_codex":[0.9565089,0.02051802,0.004436715,0.003262508,0.01437808,0.0008957526],"domain_scores_gemma":[0.7437351,0.1866894,0.02639282,0.0124105,0.02998904,0.0007832023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001661919,0.001107145,0.556102,0.002314107,0.001555773,0.0005384255,0.006276154,0.08610669,0.02339846,0.02062901,0.003380033,0.2969303],"study_design_scores_gemma":[0.0001190077,0.006051913,0.5259614,0.000482689,0.0006283486,0.0011289,0.004587446,0.4065141,0.02996972,0.01459187,0.00952882,0.0004357884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3840232,0.0004595513,0.6025971,0.0001641351,0.00008099407,0.001922168,0.002799334,0.000967234,0.006986269],"genre_scores_gemma":[0.8404754,0.0001610213,0.1545319,0.00004255785,0.00008616161,0.002034808,0.001433755,0.0001292835,0.001105028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04351008,"threshold_uncertainty_score":0.2301061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0361673203555519,"score_gpt":0.3399918087920051,"score_spread":0.3038244884364533,"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."}}