{"id":"W2776623896","doi":"10.5539/mas.v12n1p112","title":"Drag Reducer Selection for Oil Pipeline Based Laboratory Experiment","year":2017,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut Teknologi Bandung","keywords":"Reducer; Pipeline (software); Drag; Pipeline transport; Petroleum engineering; Process engineering; Computer science; Work (physics); Environmental science; Marine engineering; Mechanical engineering; Engineering; Environmental engineering; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006754169,0.0007007352,0.000557635,0.0006385826,0.0004896739,0.000428056,0.0005524773,0.0006029955,0.002926018],"category_scores_gemma":[0.0009410434,0.0002460461,0.0005240508,0.0004286669,0.0002995515,0.0004820169,0.0004444981,0.0007368677,0.0008454005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003269516,"about_ca_system_score_gemma":0.0004095573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000882286,"about_ca_topic_score_gemma":0.00136673,"domain_scores_codex":[0.9993076,0.00007790961,0.00006442607,0.0001923168,0.0002614818,0.00009614984],"domain_scores_gemma":[0.9992803,0.0001365058,0.0001507467,0.00008809436,0.0002723455,0.00007211423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002921004,0.0005225047,0.0009725851,0.0002301617,0.00001291559,0.0001062087,0.00005822552,0.001041273,0.9888527,0.0001399534,0.0003684315,0.007402838],"study_design_scores_gemma":[0.00002639263,0.002823219,0.002314277,0.00001632594,0.00004189309,0.00008198313,0.00009075457,0.003304924,0.9868084,0.0000695647,0.004393601,0.00002884544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9417194,0.001462455,0.04592358,0.0003908978,0.0002363538,0.001285427,0.001532199,0.0009764796,0.006473208],"genre_scores_gemma":[0.9004086,0.001880211,0.08519951,0.0002508123,0.0000479013,0.001381704,0.001524315,0.0001420472,0.009164838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002926018,"threshold_uncertainty_score":0.009788513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01537296197012897,"score_gpt":0.2725846902682557,"score_spread":0.2572117282981267,"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."}}