{"id":"W2079771017","doi":"10.1016/j.jcp.2015.01.010","title":"A more efficient anisotropic mesh adaptation for the computation of Lagrangian coherent structures","year":2015,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computation; Lagrangian coherent structures; Lyapunov exponent; Lagrangian; Fluid mechanics; Flow (mathematics); Anisotropy; Applied mathematics; Mathematics; Fluid dynamics; Lagrangian analysis; Classical mechanics; Computer science; Algorithm; Physics; Mechanics; Geometry; Artificial intelligence; Turbulence","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":[0.0002974025,0.0003528407,0.000411905,0.000379345,0.0002273924,0.0005845242,0.000794046,0.000728772,0.002307469],"category_scores_gemma":[0.001365789,0.0002096187,0.000486637,0.0004733016,0.0002277263,0.0007166059,0.0007116033,0.0009337136,0.0006633656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001878606,"about_ca_system_score_gemma":0.0004386937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001714357,"about_ca_topic_score_gemma":0.002683663,"domain_scores_codex":[0.9997998,0.00004673274,0.00001385076,0.00003133176,0.00009178107,0.00001657682],"domain_scores_gemma":[0.9996432,0.0001009985,0.00002050142,0.00009836861,0.0001134425,0.00002347678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003193898,0.0002780035,0.001631346,0.0001739555,0.0001086871,0.0001865267,0.0002427976,0.2705941,0.2116531,0.04397637,0.007149061,0.4636866],"study_design_scores_gemma":[0.00001359844,0.00001736952,0.000143289,0.000002873205,0.000005257433,0.00002730358,0.000006825245,0.9908222,0.005614677,0.001663513,0.001675768,0.000007283806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02451229,0.00009265589,0.9732071,0.0001221293,0.00009870866,0.0000255554,0.00004500747,0.0003154589,0.001581115],"genre_scores_gemma":[0.1957072,0.000133357,0.8002694,0.0001551467,0.00007038106,0.00006713771,0.0002185707,0.00029204,0.003086805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002307469,"threshold_uncertainty_score":0.007719278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924048645614629,"score_gpt":0.2503229598407498,"score_spread":0.2310824733846035,"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."}}