{"id":"W3007063351","doi":"10.1093/mnras/staa1532","title":"General relativistic hydrodynamics on a moving-mesh I: static space–times","year":2020,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Astrophysical Phenomena and Observations","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Texas at Austin; Nuclear Safety and Security Commission; University of Toronto; Flatiron Health; University of Texas at Austin; Canada Foundation for Innovation; Simons Foundation; Government of Ontario; National Aeronautics and Space Administration; West Virginia University; National Science Foundation","keywords":"Physics; Eulerian path; Python (programming language); Spacetime; Solver; Adaptive mesh refinement; Classical mechanics; Applied mathematics; Grid; Algorithm; Theoretical physics; Geometry; Computer science; Mathematical optimization; Quantum mechanics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000424486,0.0004551763,0.0005110864,0.0003480179,0.0005802302,0.00105949,0.001537442,0.0006755354,0.007316995],"category_scores_gemma":[0.001829222,0.0003006006,0.0007666628,0.0004236664,0.0006970094,0.0007169033,0.001166864,0.0008455144,0.001181143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008787547,"about_ca_system_score_gemma":0.001062362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008136768,"about_ca_topic_score_gemma":0.004346381,"domain_scores_codex":[0.999787,0.00004566893,0.00001231183,0.00002594273,0.00009346281,0.00003563891],"domain_scores_gemma":[0.9995987,0.00009073334,0.00005446179,0.0001012241,0.0001033242,0.00005157145],"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":[0.00008632374,0.00004049379,0.002303773,0.000106341,0.00005082151,0.0003088721,0.0001810115,0.8024757,0.01005701,0.14835,0.009362731,0.0266769],"study_design_scores_gemma":[0.00001956291,0.0000131202,0.0003462213,0.000007954591,0.000003717435,0.00005139317,0.00001662284,0.9819282,0.001606869,0.009404312,0.006590804,0.00001124039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08950131,0.0002430818,0.8659428,0.0006496342,0.0003961489,0.0001272303,0.001333489,0.004122599,0.03768368],"genre_scores_gemma":[0.5200828,0.0002212626,0.4595635,0.0003137062,0.0001658164,0.0002273052,0.001740954,0.002139842,0.01554484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008136768,"threshold_uncertainty_score":0.02447784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009333696598418829,"score_gpt":0.2021934465619021,"score_spread":0.1928597499634833,"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."}}