{"id":"W1995763733","doi":"10.1002/cjce.20054","title":"Investigation into the hydrodynamics of gas–solid fluidized beds using particle image velocimetry coupled with digital image analysis","year":2008,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Particle image velocimetry; Digital image analysis; Bubble; Mechanics; Particle tracking velocimetry; Particle (ecology); Fluidized bed; Velocimetry; Coupling (piping); Phase (matter); Materials science; Optics; Physics; Geology; Computer science; Thermodynamics; Turbulence; Composite material; Computer vision","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":[0.0002514384,0.0001791464,0.0003465661,0.0001906266,0.00008711358,0.00006799337,0.0003114053,0.00006927465,0.00001150431],"category_scores_gemma":[0.0001286078,0.0001199058,0.0001773724,0.00094706,0.0002465333,0.0002708722,0.0000136044,0.0003459365,0.000001399975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000205547,"about_ca_system_score_gemma":0.0001955145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000653354,"about_ca_topic_score_gemma":0.0001302378,"domain_scores_codex":[0.998897,0.00001346313,0.0004366743,0.00008423821,0.000260773,0.0003078539],"domain_scores_gemma":[0.9991191,0.00008808535,0.00008806837,0.0002315213,0.0001562829,0.0003169261],"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":[0.00001229295,0.000003183207,0.0005667009,0.0000248557,0.0004309936,0.00004389783,0.001428857,0.08919095,0.9082121,0.00002497411,0.00001489334,0.00004634423],"study_design_scores_gemma":[0.0002945452,0.00001409646,0.00009449987,0.0000288472,0.0002416516,0.0001197222,0.00003102311,0.6438,0.3552228,0.00002547336,0.000009009527,0.0001183467],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859535,0.0003764678,0.0133871,0.000112138,0.00006180618,0.00006537609,0.000007125884,0.00002391378,0.00001263422],"genre_scores_gemma":[0.9970686,0.000008244289,0.002786007,0.00001316101,0.0000776548,0.0000014167,0.000006086486,0.0000374747,0.000001292443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.554609,"threshold_uncertainty_score":0.4889616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006794886092667747,"score_gpt":0.1779003357356855,"score_spread":0.1711054496430178,"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."}}