{"id":"W4394938840","doi":"10.5267/j.ijdns.2024.1.018","title":"Bayesian semi-shared temporal modeling: A comprehensive approach to forecasting multiple stock prices","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Padjadjaran","keywords":"Bayesian probability; Stock (firearms); Econometrics; Computer science; Bayesian inference; Economics; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003027172,0.0009845106,0.001421369,0.001356186,0.0005916672,0.001301049,0.002085957,0.001074707,0.001383162],"category_scores_gemma":[0.005827591,0.0008728269,0.001901887,0.001590034,0.0006188584,0.00173711,0.001483818,0.001466318,0.0002444129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008353685,"about_ca_system_score_gemma":0.002075688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01877151,"about_ca_topic_score_gemma":0.01613736,"domain_scores_codex":[0.9986085,0.0005889107,0.00009027527,0.0002612077,0.0003428932,0.0001083286],"domain_scores_gemma":[0.9975642,0.001467862,0.0003724998,0.0001677806,0.0003328186,0.00009483087],"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":[0.00005737516,0.00004998694,0.002260179,0.00005433249,0.0001664641,0.00007823087,0.00009554583,0.9468286,0.0007891355,0.01451005,0.0004679722,0.034642],"study_design_scores_gemma":[0.000001870039,0.000007185136,0.0001592929,0.000003160377,0.000008764518,0.000007150124,0.000004366592,0.997113,0.00004580007,0.002527695,0.0001170445,0.000004629014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02000552,0.0002438906,0.9783154,0.0001520284,0.00002485861,0.00003248754,0.0001321074,0.000180665,0.0009129816],"genre_scores_gemma":[0.7471535,0.0009540915,0.247145,0.0001515133,0.0001759658,0.0002693431,0.0008630076,0.000100261,0.003187282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01877151,"threshold_uncertainty_score":0.03732449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3242949134289004,"score_gpt":0.4365792922831823,"score_spread":0.1122843788542819,"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."}}