{"id":"W1579955661","doi":"10.11113/matematika.v26.n.561","title":"Quarter-Sweep Improving Modified Gauss-Seidel Method for Pricing European Option","year":2010,"lang":"en","type":"article","venue":"Mathematika","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gauss–Seidel method; Mathematics; Gauss; Partial differential equation; Applied mathematics; Quarter (Canadian coin); Crank–Nicolson method; Scheme (mathematics); Iterative method; Mathematical optimization; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009451772,0.0003839781,0.0005837885,0.0004269785,0.0003477814,0.0005321804,0.0007739415,0.0007246154,0.001658876],"category_scores_gemma":[0.002129507,0.0001884847,0.0004791045,0.0003930677,0.0004097453,0.0005253297,0.0003974959,0.0007739301,0.000275313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004513715,"about_ca_system_score_gemma":0.0009330524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005668927,"about_ca_topic_score_gemma":0.004993574,"domain_scores_codex":[0.999719,0.0001311131,0.00001287985,0.00002020442,0.00009313518,0.00002375673],"domain_scores_gemma":[0.9992642,0.0003398179,0.0000655109,0.00006471452,0.0002234983,0.00004225601],"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":[0.000154469,0.00007077411,0.002866733,0.00009521092,0.00005785086,0.0001618893,0.0001220145,0.9111208,0.006914766,0.01825116,0.00114417,0.05904013],"study_design_scores_gemma":[0.000003847828,0.00001204639,0.00008855652,0.000001968827,0.000001934342,0.000007059018,0.00000393955,0.9985102,0.0003856914,0.0006577179,0.0003243684,0.000002627421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08058386,0.0004406531,0.9150565,0.0002170937,0.00008605837,0.00006269328,0.00006424204,0.0002778809,0.003211017],"genre_scores_gemma":[0.5983655,0.0004179003,0.3963659,0.0001141635,0.00005207853,0.0001543304,0.0001654066,0.0001351296,0.0042297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005668927,"threshold_uncertainty_score":0.01127189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03051653095156398,"score_gpt":0.257104875156703,"score_spread":0.226588344205139,"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."}}