{"id":"W2011275242","doi":"10.1103/physreve.70.036301","title":"Conditional Lagrangian acceleration statistics in turbulent flows with Gaussian-distributed velocities","year":2004,"lang":"en","type":"article","venue":"Physical Review E","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Acceleration; Conditional probability distribution; Turbulence; Mathematics; Probability density function; Langevin equation; Physics; Gaussian; Statistical physics; Mathematical analysis; Statistics; Classical mechanics; Mechanics; Quantum mechanics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004577033,0.0001463704,0.0002700638,0.00001742327,0.00005329835,0.00003267625,0.0000777407,0.00001116793,0.0003821162],"category_scores_gemma":[0.000012888,0.0001122392,0.00004091662,0.0001574336,0.0000295613,0.00007802642,0.00001443521,0.000140886,0.00011057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005023413,"about_ca_system_score_gemma":0.00006632707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007493098,"about_ca_topic_score_gemma":0.000005554081,"domain_scores_codex":[0.9991628,0.00002665837,0.0001967754,0.0001858037,0.0002117424,0.0002162411],"domain_scores_gemma":[0.999612,0.00005991614,0.00006264724,0.0001145375,0.0000623633,0.00008848445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008318556,0.0001856904,0.00004334101,0.0001021037,0.00002405916,0.000007489867,0.00002758083,0.0003033451,0.00006093704,0.9949997,0.0006429137,0.003594501],"study_design_scores_gemma":[0.001932981,0.0002878597,0.004144881,0.001478907,0.0001670666,0.000003246488,0.00005756891,0.01592491,0.0005622241,0.9697539,0.005154794,0.0005316167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03157039,0.0005497801,0.9625346,0.001798361,0.00005638381,0.0005912626,0.001807232,0.00003060868,0.001061358],"genre_scores_gemma":[0.9936869,0.000128929,0.0037681,0.0003195974,0.0001892713,0.00009788813,0.001783619,0.00001433052,0.0000113942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9621165,"threshold_uncertainty_score":0.457698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388334230506945,"score_gpt":0.2827704503769755,"score_spread":0.2688871080719061,"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."}}