{"id":"W4385720957","doi":"10.54254/2755-2721/8/20230252","title":"Machine Learning in Stock Price Analysis","year":2023,"lang":"en","type":"article","venue":"Applied and Computational Engineering","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Stock (firearms); Computer science; Stock price; Stock market; Machine learning; Artificial intelligence; Econometrics; Economics; 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":[0.003331246,0.0007403366,0.001064037,0.001994368,0.0004008995,0.00214375,0.0008448799,0.00145266,0.001753317],"category_scores_gemma":[0.01231543,0.0003200574,0.0005662056,0.004043931,0.001300719,0.002543612,0.0007734947,0.002586447,0.0007551911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104793,"about_ca_system_score_gemma":0.0007155825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003766267,"about_ca_topic_score_gemma":0.00194239,"domain_scores_codex":[0.9980977,0.000876936,0.0001264295,0.0002753366,0.000553261,0.00007024328],"domain_scores_gemma":[0.9948745,0.004101908,0.000343957,0.0002167556,0.0003953397,0.00006754781],"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":[0.00007665917,0.00016682,0.01437364,0.0007397457,0.0002841413,0.0002596175,0.0002970016,0.1948748,0.0007206547,0.268551,0.01850016,0.5011559],"study_design_scores_gemma":[0.00001709404,0.00005154967,0.004465605,0.000292791,0.00003724211,0.0001186578,0.0001067911,0.6108857,0.0008268219,0.3622491,0.02089353,0.00005505791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03821917,0.124286,0.7889692,0.01902167,0.001877114,0.0001408993,0.0005447427,0.0006251454,0.02631615],"genre_scores_gemma":[0.673626,0.06071179,0.250391,0.00187829,0.003872073,0.0002414606,0.0008046987,0.0001436834,0.008330951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003766267,"threshold_uncertainty_score":0.01761752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04706359813045594,"score_gpt":0.331612044878229,"score_spread":0.284548446747773,"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."}}