{"id":"W4414015827","doi":"10.11159/cist25.105","title":"Stock Price Prediction Using Kalman Filter","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kalman filter; Computer science; Stock (firearms); Econometrics; Artificial intelligence; Mathematics; Engineering","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":[0.0008553458,0.0004022603,0.0006053515,0.0004982124,0.0002800454,0.000746926,0.0004571148,0.0006203561,0.000970129],"category_scores_gemma":[0.004205847,0.0002502946,0.0004154383,0.0006202473,0.0001898645,0.00131878,0.0002320788,0.0004961031,0.0003432308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003866577,"about_ca_system_score_gemma":0.000579404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0148308,"about_ca_topic_score_gemma":0.008082735,"domain_scores_codex":[0.9996651,0.00006772023,0.00002714842,0.00007648851,0.0001288193,0.00003467028],"domain_scores_gemma":[0.9989575,0.00065609,0.0001064597,0.00005174684,0.0002149538,0.00001319034],"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":[0.0001141583,0.00005490501,0.009779843,0.000118322,0.0001319272,0.00007980483,0.0001056883,0.8295401,0.00432944,0.006037438,0.0008987082,0.1488098],"study_design_scores_gemma":[0.000004218304,0.00001922149,0.001267721,0.000007548941,0.00001311792,0.00001019245,0.000006606897,0.9962709,0.0009803028,0.001085517,0.0003268868,0.000007776932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08027693,0.0006302504,0.9156289,0.0001431362,0.00007265496,0.00002728633,0.000121271,0.000615666,0.002483922],"genre_scores_gemma":[0.9126357,0.0008782609,0.0840145,0.00004639219,0.00006343595,0.00005002137,0.0002641645,0.00003790105,0.002009687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0148308,"threshold_uncertainty_score":0.02948892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03504849683357265,"score_gpt":0.3058693558444535,"score_spread":0.2708208590108808,"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."}}