{"id":"W2897671458","doi":"10.3390/pr6100198","title":"Approximating Nonlinear Relationships for Optimal Operation of Natural Gas Transport Networks","year":2018,"lang":"en","type":"article","venue":"Processes","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gas compressor; Nonlinear system; Piecewise linear function; Mathematical optimization; Nonlinear programming; Piecewise; Natural gas; Compressor station; Linear approximation; Minification; Mathematics; Applied mathematics; Computer science; Engineering; Mathematical analysis; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007778885,0.0009214854,0.0006606162,0.0004921838,0.0004340264,0.001009918,0.0006941984,0.001046446,0.001976224],"category_scores_gemma":[0.002700214,0.0005874139,0.0005816225,0.0005647191,0.0007912785,0.0008706241,0.0006968178,0.0011996,0.0002203434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493125,"about_ca_system_score_gemma":0.001280223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01594058,"about_ca_topic_score_gemma":0.009279978,"domain_scores_codex":[0.9997222,0.0001068745,0.000009354115,0.00004239181,0.00007498319,0.00004428056],"domain_scores_gemma":[0.9994092,0.0003836559,0.000085059,0.00002298928,0.00008087651,0.000018219],"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":[0.000004910957,0.000003142961,0.0000513302,0.000008527485,0.00000156212,0.00001049599,0.0000086784,0.9973374,0.0001194955,0.001552183,0.00004343129,0.000858828],"study_design_scores_gemma":[8.727913e-7,0.000002547234,0.0000111503,0.000001507022,6.082035e-7,0.000001198042,0.000003150785,0.9992633,0.00004531494,0.0005953234,0.00007433241,5.908266e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06639533,0.0003982958,0.9218866,0.0003161861,0.00002948755,0.0000840491,0.000162229,0.0002101912,0.01051757],"genre_scores_gemma":[0.9208682,0.0004381523,0.07363644,0.000061213,0.00001797191,0.0001873804,0.000166303,0.00007988151,0.004544411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01594058,"threshold_uncertainty_score":0.0316956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244825376362575,"score_gpt":0.2156291457441235,"score_spread":0.2031808919804977,"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."}}