{"id":"W1969979660","doi":"10.1063/1.3693384","title":"Random walk of magnetic field lines in dynamical turbulence: A field line tracing method. II. Two-dimensional turbulence","year":2012,"lang":"en","type":"article","venue":"Physics of Plasmas","topic":"Solar and Space Plasma Dynamics","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Physics; Turbulence; K-omega turbulence model; K-epsilon turbulence model; Statistical physics; Field line; Field (mathematics); Turbulence modeling; Random walk; Magnetic field; Classical mechanics; Mechanics; Quantum mechanics; Statistics","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":[0.0004035527,0.0003058678,0.0002773225,0.0005920895,0.0002623316,0.0004869781,0.0005866099,0.0006265198,0.0008042399],"category_scores_gemma":[0.001771032,0.0001745212,0.0003419109,0.0005029291,0.0005405773,0.0006795262,0.0003254305,0.0004490566,0.0001896975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004380794,"about_ca_system_score_gemma":0.0004741467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00214251,"about_ca_topic_score_gemma":0.001580418,"domain_scores_codex":[0.9999019,0.00004293189,0.00000502374,0.00001384941,0.00002564646,0.00001066804],"domain_scores_gemma":[0.9995562,0.0002376824,0.00007737897,0.0000452674,0.00004889473,0.00003458605],"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":[0.0001389514,0.0001276177,0.002623675,0.0001238512,0.00004997453,0.0003002458,0.0001574691,0.7571204,0.03162393,0.1428198,0.001017399,0.06389671],"study_design_scores_gemma":[0.00000602848,0.000008112926,0.0001348655,0.000002538488,0.000001746998,0.00001910089,0.000002749662,0.9945378,0.0005420996,0.00433646,0.0004040169,0.000004499631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02929427,0.000225023,0.9693369,0.00007683282,0.0000222181,0.00003055493,0.00003545076,0.0001404258,0.0008382656],"genre_scores_gemma":[0.5572527,0.0006042615,0.4371681,0.00006849358,0.00006343822,0.00014049,0.0001780223,0.0001595202,0.004364937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00214251,"threshold_uncertainty_score":0.004260063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012106202380209,"score_gpt":0.2762919345916368,"score_spread":0.2661708725678347,"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."}}