{"id":"W4403026055","doi":"10.4018/979-8-3693-5380-6.ch021","title":"Unleashing the Power of AI for Intelligent Investments","year":2024,"lang":"en","type":"book-chapter","venue":"Advances in computational intelligence and robotics book series","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acsenda School of Management","funders":"","keywords":"Power (physics); Computer science; Business; Physics","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":[0.001002022,0.0008231304,0.0004266308,0.001313156,0.0004932964,0.004709591,0.0009587292,0.001177337,0.01548377],"category_scores_gemma":[0.002598423,0.0003799075,0.0005246056,0.001762502,0.001805071,0.004869108,0.001124589,0.003482383,0.009587829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009921456,"about_ca_system_score_gemma":0.001085521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001615011,"about_ca_topic_score_gemma":0.002571163,"domain_scores_codex":[0.9994138,0.00009386133,0.00002744247,0.00007428868,0.0003599696,0.00003064829],"domain_scores_gemma":[0.9980922,0.001442579,0.00004225099,0.0001319964,0.0002320054,0.00005888546],"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":[0.00002881497,0.00003660648,0.0003150196,0.0007324047,0.00003569702,0.00007649787,0.0002364905,0.005925425,0.001350764,0.4100879,0.08375848,0.4974158],"study_design_scores_gemma":[0.000005882442,0.00002483734,0.0003268825,0.0006315539,0.00001388113,0.0001608143,0.00009206445,0.01119656,0.0006693787,0.3026388,0.6842173,0.00002195842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004385594,0.2764227,0.1865174,0.03048593,0.005014502,0.00007175229,0.0004364409,0.001370646,0.4952952],"genre_scores_gemma":[0.09165227,0.3677202,0.2370983,0.007644381,0.007389446,0.0001470937,0.0009937373,0.0006161563,0.2867385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01548377,"threshold_uncertainty_score":0.05179834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1060135465047477,"score_gpt":0.4134106026456092,"score_spread":0.3073970561408615,"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."}}