{"id":"W2567071522","doi":"10.1115/ipc2016-64356","title":"Critical Review of Risk Criteria for Natural Gas Pipelines","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":"Risk analysis (engineering); Risk assessment; Risk management; Population; Ranking (information retrieval); Computer science; Risk management tools; Pipeline (software); Business; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001777327,0.00009045974,0.0002444898,0.00003071887,0.00002197203,0.000006494271,0.000101525,0.00005515584,0.001065755],"category_scores_gemma":[0.00220531,0.00004643936,0.0002041432,0.0000833682,0.00007765379,0.00009786715,0.00001211303,0.00006730667,0.00001506235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001500581,"about_ca_system_score_gemma":0.000004269887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002191435,"about_ca_topic_score_gemma":0.00001818625,"domain_scores_codex":[0.9993818,0.0000227554,0.0002771549,0.0001051919,0.00007995925,0.0001331267],"domain_scores_gemma":[0.9989619,0.0006036104,0.0000157054,0.0001696667,0.0002107288,0.00003835892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001297965,0.0001016174,0.0009140311,0.06062155,0.0007243003,0.00000397721,0.0002357092,0.00007336169,0.1099424,0.04801049,0.275844,0.5033988],"study_design_scores_gemma":[0.002778413,0.0003521916,0.006335308,0.03753546,0.002788703,0.00007493959,0.0003402498,0.1093333,0.4829069,0.1777704,0.1769498,0.002834303],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2998473,0.2855386,0.3408301,0.04434066,0.01021173,0.001996507,0.001506231,0.001999571,0.01372931],"genre_scores_gemma":[0.9712905,0.01935171,0.008764808,0.0001794811,0.000178251,0.00001245621,0.000005787331,0.00001194574,0.0002050418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6714432,"threshold_uncertainty_score":0.9998474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917005374412631,"score_gpt":0.3016093538846862,"score_spread":0.2824393001405599,"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."}}