{"id":"W4407309053","doi":"10.48550/arxiv.2502.04634","title":"The generic basis and flavour non-universal SMEFT","year":2025,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Los Alamos National Laboratory; National Nuclear Security Administration; Natural Sciences and Engineering Research Council of Canada; Laboratory Directed Research and Development; U.S. Department of Energy; National Science Foundation","keywords":"Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001675555,0.0002418507,0.0002444097,0.0001191955,0.0002028181,0.00007499407,0.0004317877,0.0002243774,0.00003251615],"category_scores_gemma":[0.00001934993,0.0002391009,0.0001169851,0.0002944132,0.00009209188,0.00008341599,0.0004360281,0.0003492562,0.00001496152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002013287,"about_ca_system_score_gemma":0.00008321163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006195767,"about_ca_topic_score_gemma":0.0001444858,"domain_scores_codex":[0.999065,0.00007374577,0.000153314,0.0004227435,0.00004787849,0.0002373256],"domain_scores_gemma":[0.9990333,0.0001044728,0.00005309201,0.0006217583,0.00007720823,0.0001101189],"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":[0.00001983533,0.00001546244,0.0029078,0.000225669,0.0001846509,0.00003322325,0.0002588111,0.9879065,0.00001051367,0.006488659,0.001498294,0.0004506107],"study_design_scores_gemma":[0.0003438423,0.0000086988,0.002239642,0.00005729798,0.00009174646,0.000001279806,0.0003288822,0.9883146,0.00004806757,0.0007529088,0.007488988,0.0003240362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.328043,0.0005646282,0.601564,0.0001355645,0.002495495,0.0006823667,0.0001436618,0.0006674237,0.06570385],"genre_scores_gemma":[0.9942687,0.001101837,0.000166158,0.00001930651,0.0000238375,6.603609e-7,0.0000114385,0.00001513816,0.004392948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6662257,"threshold_uncertainty_score":0.9750254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02909253058103458,"score_gpt":0.156461673643267,"score_spread":0.1273691430622324,"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."}}