{"id":"W4312889130","doi":"10.1115/ipc2022-87778","title":"Guidelines to Develop Fitness-for-Service Assessment of Exposed Pipeline Due to Flood Events: Investigation, Assessment and Mitigation","year":2022,"lang":"en","type":"article","venue":"Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransAlta (Canada)","funders":"","keywords":"Pipeline (software); Flood myth; Pipeline transport; Environmental science; Event (particle physics); Engineering; Forensic engineering; Environmental engineering; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007723791,0.0001962495,0.0003851273,0.0001446039,0.0004622551,0.0001418759,0.00009048338,0.00005951582,0.00004399299],"category_scores_gemma":[0.0002281121,0.0001834122,0.00002306823,0.0003234491,0.00002642838,0.0001892413,0.0001367492,0.00009901415,4.316591e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009698702,"about_ca_system_score_gemma":0.00008204401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003880292,"about_ca_topic_score_gemma":0.00007330596,"domain_scores_codex":[0.998508,0.00007550914,0.0007013637,0.0003101166,0.0001954684,0.0002095803],"domain_scores_gemma":[0.9989787,0.00004843762,0.00007262628,0.0001528082,0.0006175363,0.0001298792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005608976,0.00004068274,0.03648916,0.001104621,0.0002286378,0.000003444658,0.005412065,0.1200315,0.8230987,0.002941964,0.002515849,0.008077377],"study_design_scores_gemma":[0.004192625,0.001200094,0.5498446,0.001772702,0.0005391665,0.0001115879,0.0213109,0.221573,0.1805885,0.003307163,0.01317278,0.002386843],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814934,0.0001506687,0.01477661,0.001885775,0.0009638372,0.0004979412,0.0001623617,0.00005507993,0.00001438608],"genre_scores_gemma":[0.9204404,0.0001863475,0.07825831,0.000251607,0.0002419185,0.0003586082,0.000109507,0.00002226173,0.000131091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6425102,"threshold_uncertainty_score":0.7479333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03017303234665542,"score_gpt":0.2998815927172526,"score_spread":0.2697085603705972,"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."}}