{"id":"W4392215833","doi":"10.1103/physrevd.109.034518","title":"Improved algorithm for dynamical triangulations and simulations of finer lattices","year":2024,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"Office of Science; Ministry of Colleges and Universities; Alliance de recherche numérique du Canada; National Science Foundation; Government of Canada; Compute Canada; High Energy Physics; U.S. Department of Energy; Institut Périmètre de physique théorique; Innovation, Science and Economic Development Canada","keywords":"Algorithm; Computer science; Statistical physics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004004582,0.0003163101,0.001206879,0.0001283648,0.0001077287,0.0001025693,0.0006750513,0.00004123381,0.00002115204],"category_scores_gemma":[0.001152011,0.0002130529,0.0007694149,0.002443637,0.000147338,0.0005279281,0.0003206318,0.0002458591,0.00004699415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002882775,"about_ca_system_score_gemma":0.00005850881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001169797,"about_ca_topic_score_gemma":0.000002357878,"domain_scores_codex":[0.9976217,0.0001609928,0.0006688146,0.0007844661,0.0004023076,0.0003617245],"domain_scores_gemma":[0.9963741,0.002287864,0.0001968183,0.0007102122,0.0002007674,0.000230214],"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":[0.00000244692,0.0005549642,0.00004520091,0.004364293,0.0001938366,0.000003284786,0.00003200383,0.00002647328,0.001201755,0.2059631,0.002014795,0.7855979],"study_design_scores_gemma":[0.000176243,0.0001871839,0.0002996248,0.001792722,0.0007060834,0.000002398286,0.000001077849,0.8771881,0.0001749798,0.07921885,0.03995446,0.0002983009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0433809,0.2811303,0.6409274,0.02755242,0.0004159392,0.004035215,0.001271198,0.0005244765,0.0007621684],"genre_scores_gemma":[0.857504,0.08694752,0.04958341,0.003500717,0.001078023,0.0005327333,0.0004503704,0.00006203723,0.0003411688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8771616,"threshold_uncertainty_score":0.8688044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221800458588015,"score_gpt":0.427082817605102,"score_spread":0.4049027717463005,"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."}}