{"id":"W4415481482","doi":"10.1109/icivc66358.2025.11200360","title":"Stock Price Prediction and Investment Strategy via Machine Learning Model Fusion","year":2025,"lang":"","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Random forest; Support vector machine; Stock (firearms); Stock price; Unification; Investment strategy; Predictive modelling; Data modeling","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009975496,0.0005336271,0.0006677158,0.0009501414,0.001098166,0.0006678989,0.0006596922,0.0003748504,0.001057981],"category_scores_gemma":[0.005383409,0.0004344837,0.000157952,0.002097312,0.0002870054,0.0006546849,0.001173705,0.0009043245,0.00003591237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000233317,"about_ca_system_score_gemma":0.0004434416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002149568,"about_ca_topic_score_gemma":0.00005248333,"domain_scores_codex":[0.9928358,0.00169576,0.001595088,0.001589639,0.001592407,0.0006912569],"domain_scores_gemma":[0.9947623,0.003050537,0.0005275717,0.0008013017,0.0004856497,0.000372626],"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":[0.0003652391,0.000193501,0.01583507,0.00007337076,0.00008284651,0.000004942136,0.0006793974,0.08588615,0.004098203,0.0064722,0.002393363,0.8839157],"study_design_scores_gemma":[0.0009109009,0.0004726588,0.01402877,0.0001366942,0.00009231883,0.00001806495,0.0003529045,0.9131709,0.0004744167,0.06701842,0.003025093,0.0002988399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1301406,0.001518664,0.7132,0.0004564239,0.0008321609,0.000818517,0.0000153664,0.0001550456,0.1528632],"genre_scores_gemma":[0.8004221,0.0003209571,0.08759889,0.0007641313,0.00008188463,0.00004757278,0.000009086801,0.00003532022,0.1107201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8836169,"threshold_uncertainty_score":0.9998552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08529753493408301,"score_gpt":0.3745832489917547,"score_spread":0.2892857140576717,"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."}}