{"id":"W2977718562","doi":"10.1002/cjce.23649","title":"Experimental correlation for pipe flow drag reduction using relaxation time of linear flexible polymers in a dilute solution","year":2019,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Drag; Weissenberg number; Reynolds number; Dimensionless quantity; Turbulence; Mechanics; Flow (mathematics); Parasitic drag; Materials science; Relaxation (psychology); Drag coefficient; Polymer; Pipe flow; Reduction (mathematics); Thermodynamics; Mathematics; Physics; Composite material; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001024596,0.0005894863,0.0003282561,0.0008048172,0.0002047286,0.0002481589,0.0002806904,0.0004112012,0.0008522036],"category_scores_gemma":[0.001958868,0.0001738181,0.0002758411,0.000490765,0.0003548174,0.0005037452,0.0002284341,0.0006070767,0.0002570013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001844105,"about_ca_system_score_gemma":0.0002341662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005039506,"about_ca_topic_score_gemma":0.0003815226,"domain_scores_codex":[0.9995379,0.0001144912,0.0000323931,0.00009190434,0.0001872375,0.00003604154],"domain_scores_gemma":[0.9987613,0.000664023,0.0002184547,0.0000921637,0.0002217899,0.00004229529],"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":[0.0002324396,0.0001453504,0.005214471,0.000164446,0.00002135898,0.00007104906,0.00008187717,0.007156672,0.9756857,0.0004223383,0.0001879141,0.01061636],"study_design_scores_gemma":[0.00002881678,0.001276217,0.01674176,0.00003357517,0.00003098227,0.0000840781,0.00005284308,0.07134584,0.9092764,0.0002046832,0.0008700146,0.00005481491],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9343441,0.001137937,0.06175825,0.00008875318,0.00006487632,0.00009436606,0.0002611431,0.0004162387,0.00183438],"genre_scores_gemma":[0.9804967,0.000470861,0.01809074,0.00003578443,0.00001193323,0.00006951979,0.0002291882,0.00002014581,0.0005751023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001024596,"threshold_uncertainty_score":0.005418599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008810355363246434,"score_gpt":0.2110059836823631,"score_spread":0.2021956283191167,"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."}}