{"id":"W4391547860","doi":"10.2139/ssrn.4717304","title":"Cfd Stability Improvement Using Dynamic Mode Decomposition of Solution Update Vectors","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamic mode decomposition; Computational fluid dynamics; Stability (learning theory); Decomposition; Mode (computer interface); Computer science; Mechanics; Physics; Chemistry; Operating system; Machine learning","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":[0.0004818715,0.0007802061,0.0004749412,0.0005604794,0.0003022847,0.0007953111,0.0005013181,0.0005766104,0.006166914],"category_scores_gemma":[0.002618824,0.0002862899,0.0004268971,0.0003753856,0.0002763438,0.0009355271,0.0008361409,0.0009460769,0.0008515238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002560648,"about_ca_system_score_gemma":0.0005943785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00184488,"about_ca_topic_score_gemma":0.001971086,"domain_scores_codex":[0.9997786,0.00005363067,0.00001566169,0.00003569902,0.00009134253,0.00002520874],"domain_scores_gemma":[0.9993304,0.0002477618,0.00005728276,0.0001227898,0.0002149681,0.00002692142],"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":[0.0005252191,0.0002387939,0.001402227,0.0002108551,0.00007158196,0.00009617452,0.0001640629,0.4295727,0.07193929,0.02503169,0.004713831,0.4660336],"study_design_scores_gemma":[0.000008150971,0.00002733885,0.0001282238,0.000005486993,0.000003998818,0.0000144321,0.000007565662,0.9929776,0.004736876,0.001245708,0.0008401491,0.00000440564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02590396,0.0001312131,0.9689086,0.0001813788,0.0001656293,0.0000297447,0.00006261759,0.0005897637,0.00402713],"genre_scores_gemma":[0.4849838,0.0002216654,0.5068457,0.0001096922,0.0001028077,0.00009081943,0.00024337,0.0004305325,0.00697156],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006166914,"threshold_uncertainty_score":0.02063036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006549781880220039,"score_gpt":0.2665380852908072,"score_spread":0.2599883034105872,"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."}}