{"id":"W2025812132","doi":"10.1002/2015gl063147","title":"Evaluation of the inertial dissipation method within boundary layers using numerical simulations","year":2015,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Dissipation; Turbulence; Mechanics; Physics; Turbulence kinetic energy; Boundary layer; Inertial frame of reference; Computation; Spectral line; Kinetic energy; Convection; Logarithm; Computational physics; Classical mechanics; Mathematical analysis; Mathematics; Thermodynamics; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002205866,0.0006752682,0.0007934474,0.0008794973,0.0006629419,0.0009320342,0.0008062003,0.0008860662,0.0006314104],"category_scores_gemma":[0.008619821,0.0002801639,0.0004155029,0.0005981267,0.0007550497,0.0007390653,0.0006301383,0.0007322898,0.0001306332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006247465,"about_ca_system_score_gemma":0.0005061219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005309354,"about_ca_topic_score_gemma":0.001987644,"domain_scores_codex":[0.9993383,0.0002469325,0.00004999167,0.00004219121,0.0002553913,0.0000671192],"domain_scores_gemma":[0.9942899,0.00366221,0.0004680845,0.0005272229,0.0009027931,0.000149744],"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":[0.0002583331,0.0001984903,0.007418933,0.0001188768,0.00005557825,0.0001202659,0.000143599,0.9504126,0.01852266,0.004234193,0.0002354152,0.01828092],"study_design_scores_gemma":[0.00001080443,0.00005022518,0.0004973493,0.00001139929,0.000004624854,0.000005499529,0.000006263457,0.9959452,0.003173294,0.0001566719,0.0001314425,0.000007222855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8326434,0.0006975327,0.1591585,0.0002613152,0.0001425023,0.0001677113,0.0001640089,0.0006193252,0.006145771],"genre_scores_gemma":[0.9702272,0.00008487534,0.0292127,0.00001755025,0.00001254243,0.00005674573,0.00004503996,0.00005908247,0.0002842685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005309354,"threshold_uncertainty_score":0.01166588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09679808177892282,"score_gpt":0.381545717882194,"score_spread":0.2847476361032713,"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."}}