{"id":"W2932394821","doi":"10.5267/j.dsl.2019.2.001","title":"Forecasting exports and imports through artificial neural network and autoregressive integrated moving average","year":2019,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Autoregressive model; Econometrics; Artificial intelligence; Computer science; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01432229,0.0003818336,0.0006090791,0.0005763809,0.0009098388,0.001645576,0.001077552,0.0001163088,0.0002134057],"category_scores_gemma":[0.01502215,0.0002714023,0.0001108807,0.002743953,0.001126571,0.00254346,0.00104453,0.0004381143,0.00003042706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009123198,"about_ca_system_score_gemma":0.0001271366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004307981,"about_ca_topic_score_gemma":0.00001503063,"domain_scores_codex":[0.9925283,0.0003526438,0.001241698,0.00182839,0.003053132,0.0009958455],"domain_scores_gemma":[0.991592,0.005999435,0.0007717687,0.0009961294,0.0003047461,0.0003358602],"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":[0.0001540372,0.00001607924,0.1888613,0.000004525576,0.000007410461,0.0002269879,0.001966668,0.00786388,0.01820569,0.0003015681,0.004515853,0.7778761],"study_design_scores_gemma":[0.0007624019,0.0002187442,0.2717211,0.0003419856,0.00002139596,0.001026678,0.001314559,0.6642557,0.00132813,0.0520993,0.005868077,0.00104185],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604056,0.00009894035,0.03438035,0.001084836,0.002692026,0.0004318347,0.000004203715,0.00007519042,0.000827013],"genre_scores_gemma":[0.9301677,0.000004526834,0.06739555,0.002090823,0.0002054676,0.000009274736,0.000001242529,0.00002472723,0.0001006748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7768342,"threshold_uncertainty_score":0.9999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09062391350705565,"score_gpt":0.3659550999180468,"score_spread":0.2753311864109912,"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."}}