{"id":"W4385610136","doi":"10.4108/eai.28-10-2022.2328444","title":"Long Short-term Memory Neural Network Model for Stock Prediction under COVID-19 Pandemic","year":2023,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Stock (firearms); Artificial neural network; Long short term memory; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Econometrics; Term (time); Stock market; Stock price; Computer science; Business; Economics; Artificial intelligence; Recurrent neural network; Engineering; Geography; Virology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01135265,0.0002424828,0.0003821562,0.0003531382,0.0005027147,0.0002180666,0.0008146192,0.0001933957,0.0002923244],"category_scores_gemma":[0.007331177,0.0001849664,0.0002540684,0.001482861,0.0001168588,0.000343424,0.000330221,0.0002200618,0.00006368638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001814509,"about_ca_system_score_gemma":0.0002543273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001499271,"about_ca_topic_score_gemma":0.0002166087,"domain_scores_codex":[0.99586,0.0004602344,0.0008430363,0.000896106,0.001244628,0.000695997],"domain_scores_gemma":[0.9893896,0.009045607,0.0001669664,0.0007839347,0.0002178702,0.0003960028],"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":[0.0001223164,0.00001015203,0.1408549,0.000008568754,0.00001708983,0.000003117579,0.0001905922,0.7105405,0.00006603722,0.0001798974,0.08144782,0.06655895],"study_design_scores_gemma":[0.0003693276,0.00006005569,0.0558541,0.000006448415,0.00002478548,0.0000275691,0.0001559507,0.8928118,0.000005542532,0.05013658,0.0003674897,0.0001803608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2633007,0.00002825787,0.7316677,0.0004622971,0.001309882,0.0006785621,0.00002989561,0.0006987898,0.001823899],"genre_scores_gemma":[0.9414816,0.000008722126,0.02092081,0.001590611,0.0007118197,0.0002340364,0.00003706253,0.00005675133,0.03495861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7107469,"threshold_uncertainty_score":0.8776633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4144734375011664,"score_gpt":0.4773683354693301,"score_spread":0.06289489796816361,"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."}}