{"id":"W2387440810","doi":"","title":"Design of Intelligent Trading System Based on BP Neural Network","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial neural network; Backpropagation; Trading strategy; Index (typography); Layer (electronics); Artificial intelligence; Finance; Business; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004902637,0.0005573728,0.0007349037,0.0004587848,0.000560333,0.0008598353,0.001120382,0.0009137248,0.002239641],"category_scores_gemma":[0.0007729207,0.0003594074,0.0004174397,0.000341422,0.0003336593,0.0008471273,0.0003359128,0.000478476,0.0007003393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004008387,"about_ca_system_score_gemma":0.0005796388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003538111,"about_ca_topic_score_gemma":0.00210778,"domain_scores_codex":[0.9995965,0.00005584733,0.00002732932,0.0001013766,0.0001731908,0.00004581603],"domain_scores_gemma":[0.9997675,0.00004750627,0.0000237679,0.00001801835,0.0001262262,0.00001702444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005022917,0.0002559424,0.003130112,0.000447294,0.0002346756,0.0004864125,0.0003279792,0.3738236,0.08682585,0.01487214,0.005340225,0.5137535],"study_design_scores_gemma":[0.00006215752,0.0001311988,0.0006089424,0.00001550404,0.00007434485,0.000103863,0.00001445338,0.9824723,0.0110162,0.001549084,0.003929302,0.00002256079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0197277,0.0003461663,0.9718331,0.0001592687,0.0001738381,0.0000933725,0.00003099731,0.001838524,0.005797012],"genre_scores_gemma":[0.7124406,0.0004380465,0.2783889,0.0001966447,0.0001468866,0.0003419034,0.0001524573,0.00009446812,0.007800101],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003538111,"threshold_uncertainty_score":0.007492363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1243248303679173,"score_gpt":0.3798833019172614,"score_spread":0.2555584715493441,"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."}}