{"id":"W4409500994","doi":"10.5006/c2024-20705","title":"Use of AMPP SP 0113 for Methods Selection and Implementation of Pipeline Integrity Management","year":2024,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gibson Energy (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Selection (genetic algorithm); Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002554807,0.00006706825,0.0001350909,0.0001207367,0.00001347132,0.00001924243,0.00002362735,0.00004744113,0.0001461608],"category_scores_gemma":[0.00001662132,0.00005192984,0.00007575545,0.0002128257,0.00001839715,0.0001226395,0.00001329097,0.00008277482,3.767474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002855566,"about_ca_system_score_gemma":0.00000353526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005231942,"about_ca_topic_score_gemma":0.0004417567,"domain_scores_codex":[0.999508,0.000022043,0.000242451,0.0001025722,0.00005657988,0.00006836682],"domain_scores_gemma":[0.9997137,0.0001350556,0.00001593468,0.00006165259,0.00005728668,0.00001633055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004676744,0.00002615422,0.0009926253,0.005499213,0.001137378,5.918676e-7,0.0008948827,0.01143925,0.06482556,0.04541516,0.004887171,0.8648353],"study_design_scores_gemma":[0.0001399207,0.00007069776,0.002508461,0.00005079326,0.0003264651,0.000002463052,0.0009279047,0.6471569,0.3374255,0.005484095,0.005793405,0.0001133784],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3006169,0.0002143721,0.6982926,0.0001186801,0.0002105497,0.000248543,0.0000256466,0.00009325383,0.0001794701],"genre_scores_gemma":[0.8172109,0.0002324984,0.1823045,0.00000708445,0.00002364666,0.00001246188,0.00001569225,0.000007201121,0.0001860045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8647218,"threshold_uncertainty_score":0.2117637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022942281071519,"score_gpt":0.3678616464123967,"score_spread":0.3276322236016815,"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."}}