{"id":"W4409949247","doi":"10.61784/ssm3050","title":"A PREDICTIVE MODEL FOR STOCK PRICES BASED ON TRANSFORMER AND UTILIZING MULTIMODAL DATA","year":2025,"lang":"en","type":"article","venue":"Social science and management.","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Transformer; Stock (firearms); Econometrics; Computer science; Economics; Engineering; Electrical engineering; Mechanical engineering","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":[0.0007263923,0.0006451636,0.0004900201,0.0005929269,0.0002235937,0.0008425592,0.001134796,0.0004790919,0.001964676],"category_scores_gemma":[0.001999224,0.0003543607,0.0006706895,0.0006331942,0.0004091987,0.001526166,0.000732318,0.001116476,0.0005495853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006079001,"about_ca_system_score_gemma":0.0007415349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007516555,"about_ca_topic_score_gemma":0.008605978,"domain_scores_codex":[0.9997999,0.00004136349,0.000008975485,0.00007391293,0.00004797553,0.00002787119],"domain_scores_gemma":[0.9996929,0.0001535168,0.00003614875,0.0000309958,0.00007051548,0.00001590347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001774545,0.00008978371,0.002845832,0.00006332545,0.00009680734,0.0001065414,0.00009597661,0.7691542,0.0116308,0.01984797,0.001547019,0.1943443],"study_design_scores_gemma":[0.000001269963,0.000008573462,0.0001284389,0.000001424276,0.00000464366,0.000007641178,0.000002731601,0.997315,0.0005104501,0.001901838,0.0001148868,0.000003039471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01931266,0.00009579236,0.9785113,0.0001185072,0.00002307821,0.00003301677,0.0001364988,0.0005550382,0.001214224],"genre_scores_gemma":[0.8626438,0.0003143756,0.1326376,0.0001203264,0.00005426044,0.0001517861,0.0003787698,0.00007091543,0.003628017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007516555,"threshold_uncertainty_score":0.01494563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1941815827421153,"score_gpt":0.4631729553119153,"score_spread":0.2689913725698,"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."}}