{"id":"W2611819112","doi":"","title":"Pipeline Optimization Using DRA Degradation Models","year":2015,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"SNC-Lavalin (Canada)","funders":"","keywords":"Pipeline (software); Degradation (telecommunications); Environmental science; Petroleum engineering; Computer science; Geology; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000558559,0.0007902966,0.001053585,0.000545973,0.0004091413,0.001041368,0.0007189733,0.001133735,0.005092271],"category_scores_gemma":[0.001627472,0.0005888801,0.0008387734,0.0007034822,0.0003284593,0.00113264,0.0006072547,0.001007485,0.0006913069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555928,"about_ca_system_score_gemma":0.001351363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0185304,"about_ca_topic_score_gemma":0.01144738,"domain_scores_codex":[0.9997899,0.00007089016,0.000007857006,0.00004426084,0.00004813839,0.00003896727],"domain_scores_gemma":[0.9995023,0.0002458935,0.00004691797,0.00003714406,0.0001433387,0.00002441533],"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":[0.00001192506,0.000006344666,0.00005320436,0.00001147765,0.0000041437,0.000006896469,0.000003441406,0.9955349,0.0001871508,0.0009591867,0.0002747994,0.002946565],"study_design_scores_gemma":[0.000001251743,0.000003797607,0.00001362192,8.39664e-7,0.000001172782,9.637248e-7,0.000001102145,0.9994631,0.00006695783,0.0003137112,0.0001327096,7.670766e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06250697,0.000807784,0.8920148,0.0009894019,0.0001182946,0.0001254192,0.0007578228,0.001818273,0.04086112],"genre_scores_gemma":[0.9320909,0.0003614832,0.04860182,0.0001126927,0.00003451746,0.0001160982,0.0004299264,0.0003146786,0.01793776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0185304,"threshold_uncertainty_score":0.03684509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03978984286566662,"score_gpt":0.2334848723438841,"score_spread":0.1936950294782175,"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."}}