{"id":"W4378978063","doi":"10.1016/j.inffus.2023.101860","title":"Regret theory-based multivariate fusion prediction system and its application to interest rate estimation in multi-scale information systems","year":2023,"lang":"en","type":"article","venue":"Information Fusion","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Computer science; Regret; Machine learning; Artificial intelligence; Data mining; Feature selection; Multivariate statistics; Generalization; Mathematics","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":[0.005185515,0.0008314351,0.002029899,0.0008406154,0.0008363358,0.001640536,0.00158027,0.001409441,0.001639804],"category_scores_gemma":[0.009591036,0.0005007851,0.0009040931,0.001243799,0.0009436472,0.001817072,0.001801284,0.001954803,0.000477212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149854,"about_ca_system_score_gemma":0.001617392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005953149,"about_ca_topic_score_gemma":0.003851966,"domain_scores_codex":[0.9982973,0.0006910325,0.0001030075,0.000328913,0.0004423409,0.0001373358],"domain_scores_gemma":[0.996612,0.001828304,0.0002654237,0.0002293221,0.000955793,0.0001091533],"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":[0.0002146059,0.0001020621,0.001772815,0.00008411056,0.0001677801,0.000118521,0.0001271471,0.8456597,0.002150124,0.03116387,0.002860004,0.1155793],"study_design_scores_gemma":[0.000002431772,0.000009877639,0.00009883599,0.000002015674,0.000006639741,0.000009762478,0.000002650938,0.9977882,0.000168255,0.001813431,0.00009132941,0.000006595099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01081887,0.0003713653,0.9872463,0.0002802349,0.00006343025,0.00002598546,0.00004122627,0.000286607,0.0008659621],"genre_scores_gemma":[0.7850062,0.0007744297,0.209765,0.0003317409,0.0002998856,0.0001567232,0.000260043,0.0001161049,0.003289803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005953149,"threshold_uncertainty_score":0.02742398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492510837152481,"score_gpt":0.2577280080218697,"score_spread":0.2428028996503449,"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."}}