{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003204879,0.0001306056,0.0001119329,0.0001096455,0.00005227398,0.00004376731,0.00009704322,0.00004998092,0.000007249813],"category_scores_gemma":[0.00007214117,0.0001450103,0.00002459538,0.0002250001,0.000009908381,0.0004969133,0.00004854502,0.00007272407,0.00001273335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001389028,"about_ca_system_score_gemma":0.00001203911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007731188,"about_ca_topic_score_gemma":0.000007510177,"domain_scores_codex":[0.9991558,0.00002892348,0.0002268442,0.0001498246,0.0002163055,0.0002223344],"domain_scores_gemma":[0.9995888,0.00002045853,0.00003749779,0.0001497921,0.0001155226,0.00008791371],"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":[0.000003001894,0.000006840809,0.00007731102,0.00001359218,0.00001022258,0.000001877242,0.0003730469,0.9956623,0.00007208359,0.0001806591,0.002390483,0.001208521],"study_design_scores_gemma":[0.000207904,0.000008087807,0.000006752725,0.00003334093,0.00001807862,0.000002357618,0.0005100358,0.9968464,0.0006223962,0.0001378776,0.001443704,0.0001630079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04389361,0.0002097208,0.9306808,0.00004493817,0.0007585867,0.0000958692,0.000004315981,0.0005059186,0.02380624],"genre_scores_gemma":[0.8867928,0.00001935124,0.1122756,0.00005115584,0.0004812193,0.00001043766,0.0000450469,0.00006371752,0.0002606899],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8428991,"threshold_uncertainty_score":0.5913348,"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."}}