{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003656941,0.0001999536,0.0003236086,0.0003902075,0.0002061719,0.0004203632,0.0002158619,0.0001794171,0.0004672149],"category_scores_gemma":[0.0004091889,0.0001923265,0.0001188211,0.0002287534,0.0004031634,0.0002859066,0.0001798331,0.0002366219,0.0000816938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005946652,"about_ca_system_score_gemma":0.0004181849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004712323,"about_ca_topic_score_gemma":0.002854488,"domain_scores_codex":[0.9998407,0.00003123852,0.000008259578,0.00002242216,0.00007182924,0.00002553293],"domain_scores_gemma":[0.9998423,0.00007334434,0.00001906701,0.000009902799,0.00003723552,0.00001822491],"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":[0.0001119264,0.00006271915,0.001795092,0.00004529653,0.000005872109,0.0000514481,0.00002946329,0.004457981,0.9870536,0.0003875712,0.00005111281,0.005947936],"study_design_scores_gemma":[0.00004713685,0.0002389979,0.01289056,0.00000556174,0.00001072985,0.00005328027,0.00004071267,0.1193403,0.8663151,0.0002209126,0.0008137461,0.00002302142],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729407,0.0003727605,0.02590733,0.00004340069,0.00001546158,0.00003496488,0.00008454133,0.0001311657,0.0004697648],"genre_scores_gemma":[0.9852444,0.0001880672,0.01414619,0.00001256614,0.00000472588,0.00001709409,0.00008747914,0.000008272596,0.0002912341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004712323,"threshold_uncertainty_score":0.009369791,"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."}}