{"id":"W4366778062","doi":"10.54097/hset.v44i.7352","title":"Stock Price Prediction using LSTM Model","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Stock (firearms); Computer science; Deep learning; Stock price; Artificial intelligence; Stock market; Machine learning; Long short term memory; Visualization; Econometrics; Artificial neural network; Economics; Recurrent neural network; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002160201,0.00050132,0.000395783,0.0005308325,0.0001680982,0.0005371891,0.0003978814,0.0005499539,0.002259735],"category_scores_gemma":[0.0009843248,0.0001961234,0.0004108151,0.0006632752,0.0001073305,0.000924908,0.0002219562,0.0006785775,0.0005473102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004205207,"about_ca_system_score_gemma":0.0004067768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01171661,"about_ca_topic_score_gemma":0.008337241,"domain_scores_codex":[0.9998908,0.00001320567,0.000009112807,0.00003157628,0.00003733358,0.00001807753],"domain_scores_gemma":[0.9998031,0.00007148118,0.00002614652,0.00001126224,0.00007887858,0.000009158215],"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":[0.0002177491,0.0001242934,0.008135939,0.00008792338,0.0001085119,0.0002072156,0.00003223887,0.8187284,0.006711766,0.003134586,0.006527533,0.1559838],"study_design_scores_gemma":[0.000002170165,0.000005425669,0.0003130419,0.000001415069,0.00000320792,0.000004662633,0.000001060154,0.9985613,0.0004850694,0.000529261,0.00009119808,0.000002142662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4599664,0.001929982,0.5175976,0.001315408,0.0004182602,0.0000599849,0.002064464,0.00396263,0.0126853],"genre_scores_gemma":[0.9704312,0.0004762783,0.02431683,0.00007497094,0.00006191338,0.00002730729,0.0008974382,0.00002900239,0.003685094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01171661,"threshold_uncertainty_score":0.02329683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08477654353445903,"score_gpt":0.3620232368108505,"score_spread":0.2772466932763915,"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."}}