{"id":"W2952077562","doi":"10.48550/arxiv.1311.5685","title":"Data Challenges in High-Performance Risk Analytics","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Analytics; Pipeline (software); Risk management; Risk analysis (engineering); Data analysis; Portfolio; Data science; Computer science; Business; Finance; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02614218,0.001585425,0.002552888,0.00375559,0.002048921,0.01678582,0.004100332,0.003868503,0.002568353],"category_scores_gemma":[0.09778427,0.0009405275,0.001274019,0.007393888,0.004360512,0.0211195,0.00742237,0.01039536,0.002034932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002673083,"about_ca_system_score_gemma":0.003383031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003471736,"about_ca_topic_score_gemma":0.001503883,"domain_scores_codex":[0.972059,0.008778613,0.002154338,0.002589146,0.01371463,0.0007041779],"domain_scores_gemma":[0.8888242,0.07807929,0.004925067,0.01179534,0.01433075,0.002045389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004440088,0.0002614525,0.01744183,0.001522414,0.0004007034,0.001195174,0.001113621,0.1021928,0.002466804,0.497807,0.07878616,0.296368],"study_design_scores_gemma":[0.0000311826,0.00003685115,0.001616121,0.0002518766,0.00003305433,0.0004512073,0.0007125431,0.1231007,0.001663202,0.812737,0.05928033,0.00008610728],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03295011,0.02373128,0.7793572,0.1264351,0.00210602,0.0004587981,0.009255377,0.004251973,0.02145412],"genre_scores_gemma":[0.5623159,0.01888021,0.3901454,0.00773671,0.004743191,0.0006332801,0.01118835,0.00102845,0.003328613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02614218,"threshold_uncertainty_score":0.1382547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3791707720152268,"score_gpt":0.2781383826847389,"score_spread":0.1010323893304879,"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."}}