{"id":"W1988779581","doi":"10.1016/j.cam.2013.09.006","title":"An efficient fourth-order low dispersive finite difference scheme for a 2-D acoustic wave equation","year":2013,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Differential Equations and Numerical Methods","field":"Mathematics","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Mathematics; Compact finite difference; Dispersion (optics); Stability (learning theory); Wave equation; Mathematical analysis; Scheme (mathematics); Finite difference; Finite difference method; Numerical analysis; Alternating direction implicit method; Courant–Friedrichs–Lewy condition; Applied mathematics; Quantum mechanics; Discretization; Physics; Computer science","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":[0.0003858615,0.0001766341,0.0003908845,0.0001197863,0.0001314889,0.0001184549,0.0001183352,0.00006833658,0.00007711735],"category_scores_gemma":[0.0005431756,0.0001301608,0.00009225329,0.0001450171,0.00006509657,0.00009138,0.00002933289,0.0001378219,0.000006093421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002915004,"about_ca_system_score_gemma":0.00005779829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.716173e-7,"about_ca_topic_score_gemma":2.41239e-7,"domain_scores_codex":[0.9985884,0.00003073521,0.0006700435,0.0001386391,0.0003945694,0.0001775752],"domain_scores_gemma":[0.9957938,0.002714662,0.0006116031,0.0001100334,0.0006218447,0.0001480386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001358661,0.003474129,0.00001827226,0.001407689,0.0003458823,0.000003175796,0.006325517,0.2369762,0.02229887,0.6822311,0.0003835929,0.04639969],"study_design_scores_gemma":[0.0005058967,0.0001278724,0.0001777821,0.0000557621,0.00005725291,0.00001035181,0.0003505889,0.5667634,0.000194204,0.4316588,0.000003256693,0.00009483266],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3211609,0.000007830296,0.6782295,0.000119722,0.00005478115,0.0003281426,0.000006861806,0.00001070778,0.00008161043],"genre_scores_gemma":[0.4398102,0.000002294016,0.5600013,0.00004160739,0.0000738261,0.00002514584,0.000005538249,0.00001387985,0.00002625856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3297872,"threshold_uncertainty_score":0.5307804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05495404115607757,"score_gpt":0.3177952571905689,"score_spread":0.2628412160344914,"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."}}