{"id":"W4323804483","doi":"10.1038/s41598-023-30710-z","title":"Quantum computing reduces systemic risk in financial networks","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Systemic risk; Computer science; Cascading failure; Scalability; Context (archaeology); Convergence (economics); Quantum; Cascade; Financial institution; Mathematical optimization; Algorithm; Finance; Financial crisis; Mathematics; Business; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001019374,0.0005731767,0.0007776416,0.0003707199,0.0007927355,0.001012863,0.0008919299,0.0008004287,0.002109888],"category_scores_gemma":[0.003997635,0.000409694,0.0004579271,0.0004715215,0.001479579,0.00183828,0.001447533,0.001142937,0.0001517897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557707,"about_ca_system_score_gemma":0.001430438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003957177,"about_ca_topic_score_gemma":0.004053758,"domain_scores_codex":[0.9995115,0.0001871862,0.00001494254,0.00007753618,0.0001123804,0.00009648714],"domain_scores_gemma":[0.9981586,0.00127982,0.0001539252,0.0001902712,0.000129602,0.00008776911],"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":[0.00005561861,0.00003398095,0.0003897955,0.0000287257,0.00001669405,0.00003959986,0.00004217699,0.9399665,0.001824708,0.0462578,0.0004394692,0.01090493],"study_design_scores_gemma":[0.000008535624,0.00001668199,0.00008103505,0.000002659881,0.000004104489,0.000006564937,0.000008721298,0.9744714,0.0004571473,0.02476763,0.0001724512,0.000003001625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.267526,0.0003170242,0.7211546,0.0009569643,0.00005410715,0.00007808278,0.00005725328,0.0003908022,0.009465093],"genre_scores_gemma":[0.9424711,0.0001481116,0.05531481,0.0000988238,0.00001536355,0.00005418528,0.00003367657,0.00004286498,0.001821043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003957177,"threshold_uncertainty_score":0.01130199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009807339161982436,"score_gpt":0.2346501746635799,"score_spread":0.2248428355015975,"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."}}