{"id":"W2615369482","doi":"10.5006/c2011-11306","title":"Reducing Pipeline Failures in a Complex System Using Statistical Methods","year":2011,"lang":"en","type":"article","venue":"","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Devon Energy (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Reliability engineering; Pipeline transport; Engineering; Mechanical engineering; Programming language","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":[0.000243915,0.00008377924,0.0001553943,0.00008577165,0.00001804862,0.00001812745,0.00005094815,0.00004313606,0.0001297303],"category_scores_gemma":[0.00001006306,0.00007318018,0.0000136637,0.00009584584,0.000008376959,0.00007375427,0.00001439326,0.00005334161,0.000008840985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006714819,"about_ca_system_score_gemma":0.00000486782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807867,"about_ca_topic_score_gemma":0.000181206,"domain_scores_codex":[0.9993674,0.00006443164,0.0002624844,0.0001037468,0.00005200024,0.0001499305],"domain_scores_gemma":[0.9997976,0.00002143949,0.00001495555,0.0001083005,0.00001858031,0.00003908186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002000381,0.00004592553,0.001406147,0.001092189,0.00005100282,0.00006569257,0.004777192,0.9384433,0.01090321,0.03082166,0.004815521,0.007558166],"study_design_scores_gemma":[0.0001213678,0.000005253677,0.0006903812,0.0000479982,0.000005774433,0.00001521372,0.00029953,0.9959704,0.002445968,0.00002295568,0.0002774465,0.00009776819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004863431,0.00003040094,0.9752253,0.00000243674,0.0001732269,0.00009899252,0.000003302383,0.0002038726,0.01939908],"genre_scores_gemma":[0.5546703,2.93331e-7,0.4452307,0.000002063411,0.00002691614,0.000002617499,0.000004186301,0.00001198361,0.00005097144],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5498069,"threshold_uncertainty_score":0.2984201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08596117191133416,"score_gpt":0.3005509640469603,"score_spread":0.2145897921356261,"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."}}