{"id":"W4390214658","doi":"10.48550/arxiv.2312.14503","title":"The influence of parasitic modes on \"weakly'' unstable multi-step Finite Difference schemes","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Lattice Boltzmann Simulation Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office National d'études et de Recherches Aérospatiales; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche; Institut national de recherche en informatique et en automatique (INRIA); Université de Strasbourg; Institut National de la Santé et de la Recherche Médicale; McMaster University","keywords":"Truncation error; Initialization; Mathematics; Unit circle; Applied mathematics; Stability (learning theory); Truncation (statistics); Convergence (economics); Consistency (knowledge bases); Finite difference; Spurious relationship; Computer science; Mathematical analysis; Discrete mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001425566,0.0003286109,0.0003641025,0.0001623503,0.0001980238,0.00004600531,0.0006141939,0.0001868453,0.000004718757],"category_scores_gemma":[0.0002129342,0.0002995795,0.0001361332,0.0003729488,0.0002098725,0.000105383,0.0003877211,0.0004799398,0.0001119391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001322028,"about_ca_system_score_gemma":0.00004461602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000977025,"about_ca_topic_score_gemma":0.0001040956,"domain_scores_codex":[0.9987596,0.00005828428,0.0002668663,0.0004554756,0.0001199405,0.000339811],"domain_scores_gemma":[0.9978262,0.0009944213,0.0001334568,0.0007919716,0.0001817702,0.00007218277],"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":[0.00002044345,0.00002290603,0.008403371,0.0001778325,0.0001924668,0.00001978915,0.0001326275,0.9831569,0.0002444224,0.007536977,0.00003313277,0.00005914137],"study_design_scores_gemma":[0.0003329022,0.00002078769,0.06212602,0.0002945427,0.00009852819,1.708483e-7,0.0002666471,0.9335681,0.0005488517,0.002244841,0.0001427135,0.0003558584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765716,0.0001190015,0.02177221,0.00001743311,0.0001972566,0.0002748941,0.00005658452,0.0004239756,0.0005671137],"genre_scores_gemma":[0.9968864,0.0007663823,0.0001495385,0.00001212915,0.00002233838,0.000003360753,0.000009013142,0.00004528386,0.002105501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05372265,"threshold_uncertainty_score":0.9999456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.112251944341816,"score_gpt":0.2198713017065566,"score_spread":0.1076193573647405,"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."}}