{"id":"W4386163484","doi":"10.1142/q0449","title":"Artificial Intelligence and Beyond for Finance","year":2023,"lang":"en","type":"book","venue":"Transformations in banking, finance and regulation","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Finance; Computer science; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003731592,0.0003493313,0.0003907167,0.0007176261,0.0003278583,0.0003275943,0.0001747594,0.0003347213,0.00001211879],"category_scores_gemma":[0.00004799647,0.0003813113,0.0000857726,0.0005199041,0.0002066298,0.001977123,0.00005457229,0.0002600644,0.00006318428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000814552,"about_ca_system_score_gemma":0.00007377609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001895279,"about_ca_topic_score_gemma":0.0002206908,"domain_scores_codex":[0.9982157,0.000003739658,0.0007461731,0.0004655217,0.0002129394,0.0003559626],"domain_scores_gemma":[0.9991753,0.00009567566,0.0003896843,0.0002019964,0.0001310018,0.000006372564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003785437,0.00002211081,0.00008151957,0.0007435397,0.000008027943,0.000001854089,0.0002112179,0.0009577145,0.000005667695,0.8199405,0.004062674,0.1739273],"study_design_scores_gemma":[0.0001826265,0.00002974299,0.004015576,0.0009837133,0.00004788752,0.000004070428,0.00003326393,0.04245908,0.00004598818,0.7323237,0.2193,0.0005743923],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04213306,0.004003535,0.3202567,0.004698223,0.003317028,0.00852443,0.0004943899,0.001091647,0.615481],"genre_scores_gemma":[0.7399739,0.004177099,0.004500741,0.0007382187,0.001994054,0.0008599369,0.002388478,0.0003165071,0.2450511],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6978408,"threshold_uncertainty_score":0.9998639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856508168337619,"score_gpt":0.2424157033263933,"score_spread":0.2138506216430171,"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."}}