{"id":"W2472397582","doi":"10.3390/en9070504","title":"Application of Scaling-Law and CFD Modeling to Hydrodynamics of Circulating Biomass Fluidized Bed Gasifier","year":2016,"lang":"en","type":"article","venue":"Energies","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational fluid dynamics; Fluidized bed; Wood gas generator; Scaling; Scaling law; SCALE-UP; Mechanics; Fluidization; Column (typography); Environmental science; Engineering; Mechanical engineering; Physics; Waste management; Mathematics; Classical mechanics","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":[0.0001212174,0.0001067849,0.0002007856,0.00008641773,0.00002783273,0.000007013982,0.00008264598,0.00006568006,0.000002956434],"category_scores_gemma":[0.00002059579,0.00008683229,0.00004497407,0.0001244648,0.00003791777,0.00007484532,0.0000332062,0.00002550155,0.000002198166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001807813,"about_ca_system_score_gemma":0.000004970501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008893715,"about_ca_topic_score_gemma":0.00001104615,"domain_scores_codex":[0.999327,0.00001132519,0.0002745633,0.0001325464,0.0001139124,0.0001406569],"domain_scores_gemma":[0.9996347,0.00004159316,0.00002809351,0.0002022529,0.00004904152,0.00004425673],"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":[0.000007940672,0.000005592225,0.0001595678,0.00006505442,0.00002075937,2.540408e-7,0.0001653865,0.04007738,0.9509547,0.005349678,0.00000301257,0.003190638],"study_design_scores_gemma":[0.0003151687,0.000009738201,0.00002514214,0.00005333966,0.00001507145,0.000001205818,0.00003203383,0.4481922,0.5506404,0.0005599885,0.00004968397,0.0001060337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8486162,0.0002645802,0.150663,0.00001993509,0.00005993395,0.00007483464,0.000008694548,0.00008053658,0.0002122911],"genre_scores_gemma":[0.9957345,0.00003642569,0.00414804,0.000007216082,0.00002754761,0.00001400891,0.000004583828,0.00002493049,0.000002790898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4081148,"threshold_uncertainty_score":0.3540918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006542137904553307,"score_gpt":0.1980268561206898,"score_spread":0.1914847182161365,"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."}}