{"id":"W4400237258","doi":"10.1016/j.jcp.2024.113239","title":"Turbulence scaling from deep learning diffusion generative models","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Alliance de recherche numérique du Canada","keywords":"Scaling; Turbulence; Statistical physics; Generative grammar; Diffusion; Computer science; Artificial intelligence; Physics; Mathematics; Mechanics; Geometry; Thermodynamics","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":[0.0007606848,0.0005998308,0.0006272675,0.0007702389,0.000371129,0.001040207,0.0007130634,0.0007571356,0.001565461],"category_scores_gemma":[0.003417964,0.0005116691,0.0007775234,0.0004305752,0.000829871,0.001165881,0.0009016684,0.001361877,0.000197944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202631,"about_ca_system_score_gemma":0.000570217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0041155,"about_ca_topic_score_gemma":0.005226957,"domain_scores_codex":[0.9998574,0.00004310285,0.000006986345,0.00003243471,0.00003876899,0.00002127169],"domain_scores_gemma":[0.9988263,0.0007889607,0.0001321674,0.00008633294,0.00009366062,0.0000725283],"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":[0.00001851224,0.00001148593,0.0007697499,0.00001773597,0.00001264852,0.00003301095,0.00002159867,0.979521,0.0005922759,0.01457192,0.0003738729,0.004056212],"study_design_scores_gemma":[0.000001360497,0.000001964358,0.00006205123,0.000001353772,8.523115e-7,0.000003004165,0.000001291084,0.9952615,0.00005576684,0.00456418,0.00004522049,0.000001545949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3037192,0.0006522922,0.6868603,0.00122745,0.00009610031,0.00006444441,0.0005169434,0.0009123192,0.005951015],"genre_scores_gemma":[0.9738449,0.0002629923,0.0229108,0.00009244107,0.00004787308,0.00006775153,0.0003686882,0.000095457,0.002309075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0041155,"threshold_uncertainty_score":0.008725703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0292465390661276,"score_gpt":0.2440874315671528,"score_spread":0.2148408925010252,"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."}}