{"id":"W1530339538","doi":"10.1002/cjce.20357","title":"A new methodology for hydrodynamic similarity in bubble columns","year":2010,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sasol; ConocoPhillips; U.S. Department of Energy","keywords":"Dimensionless quantity; Similarity (geometry); Matching (statistics); Bubble; Turbulence; Mechanics; Work (physics); Scale (ratio); Dynamic similarity; Statistical physics; Mixing (physics); Distribution (mathematics); Tracking (education); Flow (mathematics); Computer science; Particle (ecology); Mathematics; Physics; Artificial intelligence; Mathematical analysis; Statistics; Geology; Thermodynamics","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":[0.0004971286,0.0001082808,0.000210658,0.0001514066,0.00002477921,0.0000328235,0.000283457,0.0001272177,0.00002066391],"category_scores_gemma":[0.000334651,0.00009855174,0.00008445498,0.0001414886,0.00002148191,0.00006047283,0.000007940081,0.0006761958,8.547457e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001481238,"about_ca_system_score_gemma":0.0002499884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654722,"about_ca_topic_score_gemma":0.01544769,"domain_scores_codex":[0.9992674,0.000006346228,0.0002665861,0.00006311525,0.00006237297,0.0003341599],"domain_scores_gemma":[0.9992757,0.0002103791,0.00002814285,0.0001225792,0.00003669471,0.0003264419],"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":[0.000006307687,0.000002461215,0.000100675,0.00004450238,0.00004192351,0.00002256153,0.0003053036,0.3194916,0.673746,0.003818443,0.0006591756,0.001761117],"study_design_scores_gemma":[0.0005436654,0.00001810951,0.0002169891,0.00004179774,0.00002415374,0.0001805702,0.000007198747,0.9706749,0.0216087,0.002311888,0.004165404,0.000206585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511093,0.0002103478,0.04695291,0.0003841514,0.001061175,0.0001079824,0.000007823411,0.00002224071,0.000144044],"genre_scores_gemma":[0.9709229,0.000001685253,0.02874735,0.00003191569,0.0002400249,0.000003027412,0.000001195358,0.0000316066,0.00002026995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6521373,"threshold_uncertainty_score":0.8620174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253519871671103,"score_gpt":0.2115527246602035,"score_spread":0.1990175259434925,"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."}}