{"id":"W2534706551","doi":"10.1016/j.ijmultiphaseflow.2016.06.023","title":"Investigation of particle-laden turbulent pipe flow at high-Reynolds-number using particle image/tracking velocimetry (PIV/PTV)","year":2016,"lang":"en","type":"article","venue":"International Journal of Multiphase Flow","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Natural Resources Limited","keywords":"Reynolds number; Turbulence; Particle image velocimetry; Particle tracking velocimetry; Mechanics; Pipe flow; Materials science; Velocimetry; Two-phase flow; Particle (ecology); Physics; Optics; Flow (mathematics); Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005539504,0.0002429143,0.000330181,0.0001416203,0.00005573222,0.00006528384,0.0004857968,0.0001139114,0.0003030632],"category_scores_gemma":[0.0004013042,0.0002032318,0.0001912845,0.0001968267,0.0001641323,0.0008884022,0.00009956628,0.0002115652,0.00009087182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007044654,"about_ca_system_score_gemma":0.00006383109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001781519,"about_ca_topic_score_gemma":0.00001038219,"domain_scores_codex":[0.997381,0.00009084812,0.001071252,0.0002000114,0.0008942336,0.0003625935],"domain_scores_gemma":[0.9981204,0.0002994495,0.0003435609,0.000253479,0.0007478283,0.0002352969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001751418,0.00006839997,0.02206234,0.00001968554,0.0003341518,0.0001982681,0.0003894767,0.08720811,0.8798664,0.00007860341,0.0003087146,0.009290665],"study_design_scores_gemma":[0.002084925,0.00003048863,0.004349147,0.0002158055,0.00004931939,0.0002669536,0.00001636165,0.571646,0.4208967,0.0002017129,0.00007345803,0.0001691027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940338,0.0001359102,0.05722383,0.000562096,0.001492716,0.0001022253,0.00005922743,0.00006402662,0.00002193573],"genre_scores_gemma":[0.9487643,0.0000635243,0.05053104,0.0000628964,0.0004751576,0.000003882466,0.00000532149,0.00005476326,0.00003907272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4844379,"threshold_uncertainty_score":0.8287551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02470200505283084,"score_gpt":0.272954768867601,"score_spread":0.2482527638147702,"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."}}