{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005044189,0.0004211116,0.0005736235,0.001254775,0.0001750363,0.0007774979,0.0003972473,0.000529091,0.001636901],"category_scores_gemma":[0.002017243,0.0001968088,0.0004798033,0.001242183,0.0001283677,0.0008490765,0.0002564826,0.0006784488,0.000652117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003683134,"about_ca_system_score_gemma":0.0003995561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005093189,"about_ca_topic_score_gemma":0.003347268,"domain_scores_codex":[0.9997533,0.00004753524,0.00002600352,0.00004431878,0.00009974255,0.0000290605],"domain_scores_gemma":[0.9995166,0.0002471219,0.00006540339,0.00003249531,0.0001226101,0.00001581787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001190715,0.0001200532,0.01243926,0.000138066,0.0001709657,0.0001695262,0.0000429926,0.4654248,0.004514299,0.007661161,0.004296735,0.5049031],"study_design_scores_gemma":[0.000003058381,0.000008256849,0.0008998161,0.000007500202,0.000006288187,0.000009898189,0.000003232235,0.9963773,0.0004898284,0.001811501,0.0003791226,0.000004244425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1570961,0.004429826,0.8250442,0.001265522,0.0003608576,0.00008317085,0.0005770933,0.00187398,0.00926911],"genre_scores_gemma":[0.8710884,0.001877196,0.1221193,0.0001116314,0.0002537485,0.00004965944,0.0006511931,0.00003184873,0.003817007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005093189,"threshold_uncertainty_score":0.01012707,"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."}}