{"id":"W2949299135","doi":"10.48550/arxiv.1208.4870","title":"Numerical solution of the Optimal Transportation problem using the Monge-Ampere equation","year":2012,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Differential Equations and Boundary Problems","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Monge–Ampère equation; Stencil; Mathematics; Laplace's equation; Solver; Convergence (economics); Partial differential equation; Boundary value problem; Applied mathematics; Mathematical analysis; Elliptic partial differential equation; Biharmonic equation; Grid; Mathematical optimization; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005337634,0.0002711699,0.0003293097,0.00005158232,0.0003638852,0.00005944676,0.0004162839,0.0002762732,0.00008266845],"category_scores_gemma":[0.00006563239,0.000165592,0.0002917949,0.0001956124,0.000165246,0.0001817088,0.0001079798,0.0005508439,0.000009011464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083848,"about_ca_system_score_gemma":0.0002017723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000711518,"about_ca_topic_score_gemma":0.00007891746,"domain_scores_codex":[0.9980496,0.0001963249,0.0007098679,0.0002926237,0.0004696153,0.0002820368],"domain_scores_gemma":[0.998201,0.0001384987,0.000768893,0.0006363417,0.0002100145,0.00004524108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002705761,0.004283625,0.6014322,0.006582638,0.002051209,0.000004781407,0.05894014,0.1233748,0.06625585,0.1181354,0.001307779,0.01736104],"study_design_scores_gemma":[0.002542338,0.0002652078,0.4084478,0.003429537,0.005338695,0.00002842849,0.003342699,0.3511781,0.02013988,0.2012858,0.00126319,0.002738253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8127866,0.00011045,0.1852225,0.0003048467,0.0004835552,0.0008640407,0.00002897298,0.00006087421,0.0001380589],"genre_scores_gemma":[0.9908003,0.00001509792,0.008634472,0.00002067115,0.0002063039,0.00008192119,0.00008476159,0.00004317844,0.0001133358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2278033,"threshold_uncertainty_score":0.6752648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1849789033617719,"score_gpt":0.3266942408165742,"score_spread":0.1417153374548023,"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."}}