{"id":"W1588662652","doi":"10.1007/978-3-540-45231-7_38","title":"Study of Canada/US Dollar Exchange Rate Movements Using Recurrent Neural Network Model of FX-Market","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Exchange rate; Computer science; Currency; Foreign exchange market; Artificial neural network; Liberian dollar; Econometrics; Artificial intelligence; Economics; Monetary economics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01302968,0.0005887589,0.001245143,0.0008054074,0.0002905729,0.0001460948,0.002819921,0.0002069479,0.00009748839],"category_scores_gemma":[0.002598707,0.0004827752,0.0001531835,0.001562996,0.0004980924,0.0002081949,0.001392816,0.0006060804,4.055775e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004443586,"about_ca_system_score_gemma":0.001430082,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004162377,"about_ca_topic_score_gemma":0.04497109,"domain_scores_codex":[0.9910765,0.0006835472,0.001778996,0.001646381,0.003895881,0.000918713],"domain_scores_gemma":[0.992135,0.003454997,0.001621126,0.001636556,0.0009454431,0.0002069149],"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":[0.00004963059,0.00005676399,0.001470022,0.00002331538,0.00002136819,0.00002377643,0.0005657236,0.8678382,0.00004588606,0.00004685704,0.0003143621,0.1295441],"study_design_scores_gemma":[0.0004265627,0.0002816737,0.0007358968,0.0002683512,0.00002457973,0.00001030123,0.00000313719,0.9565995,0.0001746406,0.04086288,0.0001661945,0.0004462264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08650066,0.0003801251,0.9032322,0.00004570974,0.00440783,0.001094813,0.00003475356,0.00001691322,0.004287041],"genre_scores_gemma":[0.6361957,0.00001671373,0.3602845,0.001240991,0.0005038803,0.00001439849,0.000002215663,0.0001024106,0.001639124],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5496951,"threshold_uncertainty_score":0.9997624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383763842022073,"score_gpt":0.3590223381309064,"score_spread":0.2206459539286991,"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."}}