{"id":"W1540341627","doi":"10.1109/icsmc.2003.1244507","title":"A sequential learning neural network for foreign exchange rate forecasting","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pound (networking); Artificial neural network; Random walk; Computer science; Exchange rate; Us dollar; Multilayer perceptron; Artificial intelligence; Liberian dollar; Econometrics; Machine learning; Economics; Statistics; Mathematics; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006331792,0.0004062484,0.000475516,0.0003569116,0.0002807739,0.0003667143,0.0005481317,0.0004540689,0.001315598],"category_scores_gemma":[0.001235615,0.0002001558,0.0002753303,0.0004040726,0.0002051524,0.0005114692,0.0002655666,0.0004682082,0.0001814717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004693862,"about_ca_system_score_gemma":0.000611611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017632,"about_ca_topic_score_gemma":0.008409259,"domain_scores_codex":[0.9998202,0.00005840976,0.00001298666,0.00004290562,0.00004513492,0.00002034561],"domain_scores_gemma":[0.9997715,0.0001013588,0.00001919533,0.00001336393,0.00008162853,0.00001287124],"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":[0.0001702746,0.00006596632,0.001226905,0.00005329552,0.00003998645,0.00005724758,0.00002161819,0.8447745,0.002397048,0.004906693,0.00109777,0.1451886],"study_design_scores_gemma":[0.000003099605,0.00001112898,0.00006564122,0.000001051573,0.000002907276,0.000003631919,8.202132e-7,0.9990649,0.0001605423,0.0005787491,0.0001065477,0.000001110903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09423807,0.0008641114,0.899013,0.0003713098,0.0001713338,0.00005967235,0.0001576836,0.0007381433,0.004386653],"genre_scores_gemma":[0.8788987,0.0004335936,0.1161356,0.00009694233,0.00006531258,0.0001043304,0.0002057092,0.00002200196,0.004037991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01017632,"threshold_uncertainty_score":0.02023417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308473825625004,"score_gpt":0.2210095538330275,"score_spread":0.1979248155767774,"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."}}