{"id":"W11382371","doi":"10.71781/10371","title":"Sequential Machine learning Approaches for Portfolio Management","year":2009,"lang":"en","type":"dissertation","venue":"The American Journal of Medicine","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Portfolio; Artificial intelligence; Machine learning; Project portfolio management; Set (abstract data type); Futures contract; Representation (politics); Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.02064789,0.000325704,0.001337531,0.0009128962,0.000227679,0.00006488417,0.001671975,0.00005929487,0.0002115284],"category_scores_gemma":[0.005340077,0.0001639713,0.0003945521,0.001093171,0.0003797242,0.00008247206,0.00004520219,0.0008399748,0.000005570891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007460616,"about_ca_system_score_gemma":0.0001136489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003250655,"about_ca_topic_score_gemma":0.00001318453,"domain_scores_codex":[0.9941224,0.001014316,0.001689064,0.0003434949,0.002498981,0.0003317004],"domain_scores_gemma":[0.9902351,0.002724794,0.005804081,0.0004917532,0.0005789148,0.0001653089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001716834,0.00002537208,0.00007657013,0.0000174621,0.0002127644,0.00003827839,0.0008055552,0.0004247503,0.00003761265,0.0002714764,0.01057734,0.985796],"study_design_scores_gemma":[0.01187126,0.02793482,0.1199846,0.003910447,0.006794609,0.003315993,0.135606,0.01769116,0.0004134715,0.240227,0.4300942,0.002156523],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5332536,0.01220078,0.2343986,0.02438711,0.01248055,0.00296186,0.0000258517,0.0001293895,0.1801623],"genre_scores_gemma":[0.8142486,0.001326686,0.08676445,0.001781941,0.007597232,0.00004445706,0.0001467812,0.0002035953,0.08788624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9836395,"threshold_uncertainty_score":0.7156189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1514687961409382,"score_gpt":0.4297605850729527,"score_spread":0.2782917889320146,"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."}}