{"id":"W7015393322","doi":"","title":"Stock Market Prediction using LSTM and Markov Chain Models: A Case Study of Royal Bank of Canada Stock","year":2023,"lang":"en","type":"other","venue":"UVic’s Research and Learning Repository (University of Victoria)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Markov chain; Stock (firearms); Stock market; Probabilistic logic; Markov model; Predictive power; Markov process; Closing (real estate)","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":[0.002007256,0.000363479,0.0008663841,0.001245442,0.0008231935,0.00003811459,0.0003606864,0.0004001017,0.0001995696],"category_scores_gemma":[0.0002159273,0.0004659549,0.00008097139,0.0008271701,0.0005255067,0.0001685591,0.0005838458,0.001368411,0.000001063123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006460905,"about_ca_system_score_gemma":0.001193048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.835916,"about_ca_topic_score_gemma":0.5536034,"domain_scores_codex":[0.994455,0.001857307,0.0003841706,0.0008239756,0.001861354,0.0006182048],"domain_scores_gemma":[0.9970751,0.0005638011,0.0007093009,0.0005764127,0.0006827493,0.0003926662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01038728,0.003514868,0.2923606,0.009937313,0.009107204,0.03189164,0.0604633,0.01634235,0.005430441,0.00005758889,0.555611,0.004896459],"study_design_scores_gemma":[0.01644912,0.01304443,0.04710791,0.005953585,0.001715019,0.00166565,0.3504182,0.504097,0.00005529768,0.00004088385,0.05678793,0.002664932],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569127,0.0008243477,0.00005207958,0.0000065936,0.0004056202,0.001396323,0.0002839803,0.0001851204,0.03993322],"genre_scores_gemma":[0.7640635,0.00007539866,0.0002033446,2.757613e-7,0.0002185164,0.000002272028,0.00001261216,0.0004790993,0.234945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.498823,"threshold_uncertainty_score":0.9997792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03710220250265592,"score_gpt":0.2668137253521368,"score_spread":0.2297115228494809,"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."}}