{"id":"W3109951759","doi":"10.1002/cjce.23949","title":"Two‐phase flow‐patterns identification in oil/gas pipelines based on fractal analysis","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline transport; Fractal; Flow (mathematics); Fractal analysis; Pipeline (software); Petroleum engineering; Two-phase flow; Multiphase flow; Mechanics; Fractal dimension; Engineering; Mathematics; Physics; Mechanical engineering; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003269541,0.000104258,0.0003746342,0.0004450953,0.00003372266,0.00009068795,0.0002607763,0.00004020959,0.0003755424],"category_scores_gemma":[0.0002195632,0.00009785671,0.000249067,0.0007517679,0.00001405211,0.00008472327,0.000007502718,0.0002312656,0.00002192225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468179,"about_ca_system_score_gemma":0.00004802764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004700597,"about_ca_topic_score_gemma":0.001518768,"domain_scores_codex":[0.9989407,0.000007742557,0.0006782888,0.0001351856,0.00005330837,0.0001847867],"domain_scores_gemma":[0.9992282,0.0000481882,0.0002478772,0.0001621388,0.00004006676,0.0002735091],"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":[0.00003169815,0.00003125298,0.009598118,0.00004373464,0.0003795625,0.000057056,0.0005262406,0.9834158,0.001833809,0.001986786,0.0001468465,0.00194904],"study_design_scores_gemma":[0.000465468,0.00001889492,0.000763784,0.00001971446,0.00005375679,0.000002738344,0.00001634698,0.9965392,0.0005910202,0.00007630768,0.001335668,0.0001170801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772128,0.0004159074,0.01605778,0.00576935,0.0001487465,0.0000365978,0.0001093173,0.000007950506,0.0002415149],"genre_scores_gemma":[0.9993501,0.00000265729,0.0001781805,0.0001961939,0.0002301682,0.000001769384,0.00001212489,0.0000129585,0.00001581136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0221373,"threshold_uncertainty_score":0.7105928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01906004076277389,"score_gpt":0.2030883592545991,"score_spread":0.1840283184918252,"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."}}