{"id":"W2032434662","doi":"10.1175/jas3872.1","title":"Statistics and Parameterizations of the Effect of Turbulence on the Geometric Collision Kernel of Cloud Droplets","year":2007,"lang":"en","type":"article","venue":"Journal of the Atmospheric Sciences","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Turbulence; Physics; RADIUS; Dissipation; Collision; Range (aeronautics); Mechanics; Turbulence kinetic energy; Collision frequency; Flow (mathematics); Cluster analysis; Statistical physics; Computational physics; Classical mechanics; Statistics; Mathematics; Thermodynamics; Plasma; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001819092,0.00007853584,0.0001839009,0.00001370007,0.0001003035,0.00001503416,0.000650174,0.00002801901,0.000004812022],"category_scores_gemma":[0.001254573,0.00003412989,0.0000664028,0.001541321,0.0005193647,0.00006352957,0.00007381967,0.0001301467,2.527476e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003025186,"about_ca_system_score_gemma":0.00003031418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001073292,"about_ca_topic_score_gemma":0.000002749061,"domain_scores_codex":[0.9987582,0.00009568699,0.0004178963,0.00006009591,0.0005376808,0.0001304647],"domain_scores_gemma":[0.9976667,0.001641232,0.0003677529,0.000209793,0.00008469028,0.00002982294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003593749,0.00003546723,0.0547594,0.00005988783,0.00004764068,0.000001276842,0.0003921196,0.9046201,0.03597512,0.001002076,0.0002789732,0.002792013],"study_design_scores_gemma":[0.0002662269,0.0006066064,0.145347,0.000196889,0.00006561486,0.00002531998,0.0001411535,0.7873633,0.06517576,0.0007029046,0.00003232211,0.00007696021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932428,0.0002962146,0.005481177,0.00006581354,0.0006958302,0.0001167379,0.000008678663,0.000002809806,0.00008994898],"genre_scores_gemma":[0.9958764,0.00009613602,0.003975569,0.00001248569,0.00002410654,5.143042e-7,2.611836e-8,0.000005161977,0.000009612607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1172568,"threshold_uncertainty_score":0.1913621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007683464043227181,"score_gpt":0.2332999214524482,"score_spread":0.2256164574092211,"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."}}