{"id":"W4413679998","doi":"10.1109/compsac65507.2025.00264","title":"Hybrid LSTM/GRU and Support Vector Regression Models for Stock Index Prediction","year":2025,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Computer science; Artificial intelligence; Support vector machine; Regression; Index (typography); Regression analysis; Machine learning; Econometrics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004842135,0.0001720876,0.0003162038,0.0004329591,0.0002520196,0.000190144,0.0003935391,0.00009991714,0.0002572348],"category_scores_gemma":[0.005954112,0.0001157909,0.0001040798,0.0004505396,0.00008140753,0.0004134197,0.0002383698,0.0001295398,0.000006658121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005027414,"about_ca_system_score_gemma":0.0001470783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001497963,"about_ca_topic_score_gemma":0.000008324931,"domain_scores_codex":[0.9974678,0.0002291071,0.0006112684,0.0006783305,0.0007304086,0.0002831163],"domain_scores_gemma":[0.9954357,0.003346117,0.0001738199,0.0005611947,0.0003675646,0.0001156672],"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":[0.0005056203,0.00005843886,0.02371761,0.00002740822,0.00003223118,0.000002782181,0.0001936051,0.0004446318,0.0005402487,0.006053318,0.2778982,0.6905259],"study_design_scores_gemma":[0.000921903,0.0001896413,0.0240582,0.00006092889,0.00002554897,0.00001772666,0.0001233,0.6725609,0.002283339,0.2777427,0.02184711,0.0001686639],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07878666,0.00006032919,0.8799112,0.0006275819,0.001498232,0.0006464928,0.00004648073,0.0001354173,0.03828754],"genre_scores_gemma":[0.8636302,0.000007527208,0.05818549,0.0003389475,0.0001111049,0.0001122611,0.000008416849,0.00001741067,0.07758868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8217258,"threshold_uncertainty_score":0.7128059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1136664192466115,"score_gpt":0.4160075313185488,"score_spread":0.3023411120719373,"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."}}