{"id":"W1852637228","doi":"10.1175/jas-d-15-0203.1","title":"Cloud Droplet Collisions in Turbulent Environment: Collision Statistics and Parameterization","year":2015,"lang":"en","type":"article","venue":"Journal of the Atmospheric Sciences","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Collision; Physics; Statistical physics; Direct numerical simulation; Reynolds number; Taylor microscale; Adiabatic process; Range (aeronautics); Computational physics; Mechanics; Computer science; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000765231,0.0003148945,0.0003380846,0.0006430727,0.0002640044,0.0006567424,0.0005314532,0.0003389466,0.000290764],"category_scores_gemma":[0.004307569,0.0001645098,0.0002421336,0.0007867598,0.0004505391,0.000866999,0.0004431762,0.0003400655,0.00005951735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006398473,"about_ca_system_score_gemma":0.00044458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003456084,"about_ca_topic_score_gemma":0.001434341,"domain_scores_codex":[0.9997148,0.00006843125,0.00002698554,0.00005463626,0.00009979409,0.00003544954],"domain_scores_gemma":[0.998153,0.001048335,0.0003217047,0.0002340322,0.0001902493,0.00005252121],"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":[0.0001196297,0.00006914055,0.0185109,0.00002179039,0.00002154646,0.00007680032,0.00003753204,0.9609623,0.01052184,0.002987101,0.00006341004,0.00660796],"study_design_scores_gemma":[0.000003038212,0.00001038843,0.001609842,0.00000100012,0.000001957084,0.00001297699,0.000004460584,0.9945822,0.003514435,0.0002248484,0.00002935107,0.000005371114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9076607,0.0001067152,0.09130711,0.00002976892,0.000008052411,0.00002876845,0.0001043928,0.0001449859,0.0006096439],"genre_scores_gemma":[0.9948544,0.00002131801,0.004981972,0.000002522918,0.000001945236,0.00000909076,0.00005708577,0.00001359316,0.00005820358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003456084,"threshold_uncertainty_score":0.006871939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848953525792161,"score_gpt":0.231954746302917,"score_spread":0.2134652110449954,"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."}}