{"id":"W2565679993","doi":"10.1115/ipc2016-64635","title":"Improving Safety Through Engineering Assessments for Change in Location Class","year":2016,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Pipeline transport; Context (archaeology); Integrity management; Reliability engineering; Risk analysis (engineering); Safety factor; Reliability (semiconductor); Computer science; Class (philosophy); Safety engineering; Well control; Functional safety; Engineering; Business; Structural engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004476803,0.0008759935,0.0004039299,0.001490044,0.001058563,0.00202231,0.0013534,0.001091841,0.003113755],"category_scores_gemma":[0.01165861,0.0004120682,0.0006893057,0.0004787605,0.0009194906,0.002095669,0.001662159,0.001005455,0.0007394391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003251967,"about_ca_system_score_gemma":0.005227927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02163992,"about_ca_topic_score_gemma":0.05038471,"domain_scores_codex":[0.9957303,0.0007727093,0.0001456287,0.0004736504,0.002594895,0.0002826868],"domain_scores_gemma":[0.9907923,0.001775624,0.002152032,0.0009048548,0.004122645,0.0002526059],"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":[0.000515269,0.0007668298,0.104473,0.0003460506,0.00009913763,0.0007190765,0.002084359,0.306839,0.09137624,0.01525092,0.003291497,0.4742386],"study_design_scores_gemma":[0.0001222252,0.004102404,0.2051785,0.0004260359,0.0002862147,0.0008033937,0.004432403,0.6011937,0.1075038,0.03183828,0.04358988,0.0005232426],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5797937,0.0002761697,0.3753196,0.001197538,0.0001088934,0.000652414,0.0003609021,0.00240869,0.03988213],"genre_scores_gemma":[0.9185007,0.0001158485,0.07503624,0.00008370782,0.00001487458,0.00008107872,0.0001557928,0.00007680333,0.005934975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02163992,"threshold_uncertainty_score":0.04302794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02426929712229116,"score_gpt":0.2786629672830461,"score_spread":0.254393670160755,"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."}}