{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007394063,0.0005428257,0.0003280922,0.0007367142,0.001013997,0.001019165,0.001130819,0.001010245,0.002312792],"category_scores_gemma":[0.003311936,0.0002250313,0.0004075028,0.001464818,0.0004556641,0.0008241581,0.0003628964,0.0008658176,0.0004507483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006650071,"about_ca_system_score_gemma":0.004595017,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8676468,"about_ca_topic_score_gemma":0.8674152,"domain_scores_codex":[0.9996954,0.00005535487,0.0000189674,0.00006414814,0.0001093322,0.00005692508],"domain_scores_gemma":[0.9989032,0.0005822095,0.00005733472,0.00007062993,0.0003055655,0.00008111959],"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":[0.0007637385,0.0007047267,0.08568542,0.0004108607,0.0002428356,0.006251339,0.002021556,0.7120847,0.004223283,0.009968721,0.027658,0.1499848],"study_design_scores_gemma":[0.00003371574,0.0000457727,0.01516841,0.00002052687,0.00002811709,0.0001087203,0.0004235442,0.9778218,0.00152387,0.001276659,0.003521894,0.00002689192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785339,0.000628867,0.006731431,0.001623031,0.00004110156,0.0000824184,0.002553313,0.00053626,0.009269732],"genre_scores_gemma":[0.9855341,0.0003387487,0.006698713,0.00007639526,0.00001371238,0.00001927894,0.001645398,0.00003882064,0.005634857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1323532,"threshold_uncertainty_score":0.2662652,"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."}}