{"id":"W4388854784","doi":"10.1109/tnnls.2023.3332315","title":"Federated Learning for Data Trading Portfolio Allocation With Autonomous Economic Agents","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks and Learning Systems","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Leverage (statistics); Portfolio; Profitability index; Revenue; Artificial intelligence; Business; Finance","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":[0.002109226,0.0008091184,0.001276302,0.0004769844,0.0006081643,0.001144299,0.001816442,0.001543368,0.001810797],"category_scores_gemma":[0.00405943,0.0004076048,0.000550814,0.0006711807,0.0008902933,0.00182066,0.001653599,0.001584453,0.0003389809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009159868,"about_ca_system_score_gemma":0.001398578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005007504,"about_ca_topic_score_gemma":0.003818473,"domain_scores_codex":[0.9993679,0.0001887578,0.00004015323,0.000147067,0.0001358198,0.0001203297],"domain_scores_gemma":[0.9984953,0.000784623,0.0001779309,0.0001825335,0.0002452383,0.0001143739],"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":[0.000124381,0.0001351692,0.001067138,0.00002417369,0.00003612513,0.00007850508,0.00004010955,0.9454507,0.0008781322,0.004892849,0.0006718977,0.04660085],"study_design_scores_gemma":[0.000006684427,0.00001431135,0.00003512628,0.000001120324,0.000002080398,0.000005838958,0.000003208946,0.9980817,0.0001672272,0.001572301,0.0001086611,0.000001710221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07197907,0.0004140669,0.923741,0.000486519,0.00007291762,0.0000681064,0.00004910566,0.0007774003,0.002411761],"genre_scores_gemma":[0.9239267,0.0001094205,0.07359286,0.0002633367,0.00003575794,0.00008523144,0.00007939898,0.0000305031,0.00187685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005007504,"threshold_uncertainty_score":0.01115483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1404355492229614,"score_gpt":0.3683006832014061,"score_spread":0.2278651339784448,"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."}}