{"id":"W4393436133","doi":"10.54097/gdm0kc53","title":"Stock Price Prediction Using Machine Learning Techniques","year":2024,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Stock price; Stock (firearms); Computer science; Machine learning; Artificial intelligence; Econometrics; Economics; Engineering; Geology; Mechanical engineering; Series (stratigraphy)","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":[0.005523236,0.0001710367,0.0002380028,0.003997626,0.0002261009,0.0002994933,0.0006529186,0.0001731193,0.00001108903],"category_scores_gemma":[0.005025624,0.000129917,0.00002705354,0.007606739,0.0004241226,0.0004962751,0.000340458,0.0005035408,0.00001974982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001504248,"about_ca_system_score_gemma":0.00008721159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002043836,"about_ca_topic_score_gemma":0.000003675603,"domain_scores_codex":[0.9976009,0.00005250483,0.0004397277,0.0007809382,0.0006883112,0.0004375888],"domain_scores_gemma":[0.9986662,0.0007068896,0.00006249204,0.0003620845,0.0001261875,0.00007620862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001338257,0.00004122981,0.02044104,0.00005734397,0.00001540882,0.0001600045,0.0007557485,0.005953212,0.5054666,0.1626898,0.0001011956,0.304305],"study_design_scores_gemma":[0.00007386184,0.0001074331,0.00183553,0.0001884392,0.000005917788,0.0002770369,0.00006450488,0.8762324,0.05503533,0.007302435,0.05865679,0.0002203639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8770043,0.001531095,0.1157317,0.001016838,0.001389525,0.0002521674,0.000005354874,0.002003749,0.001065302],"genre_scores_gemma":[0.8948376,0.00005763692,0.1047811,0.000004268663,0.00006679137,0.00001829954,2.791706e-7,0.00001707525,0.000216979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8702791,"threshold_uncertainty_score":0.6016505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04354629445933152,"score_gpt":0.3476893721341712,"score_spread":0.3041430776748397,"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."}}