{"id":"W4401329460","doi":"10.1109/fuzz-ieee60900.2024.10612046","title":"Stock Market Index Prediction: A Framework Based on Transfer Learning and Knowledge Graph Enrichment Through Uncertainty Using Natural Language and Fuzzy Logic","year":2024,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fuzzy logic; Computer science; Artificial intelligence; Index (typography); Natural language; Stock market; Knowledge graph; Natural language processing; Machine learning; Programming language; Geography","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":[0.00130081,0.0006612256,0.0008751862,0.001572787,0.0005623499,0.001400564,0.001954736,0.001090337,0.001877681],"category_scores_gemma":[0.002859527,0.0004195933,0.001345698,0.001049052,0.001102185,0.002330365,0.001565617,0.001275442,0.0002745586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001472421,"about_ca_system_score_gemma":0.001598409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01197703,"about_ca_topic_score_gemma":0.008704206,"domain_scores_codex":[0.9993481,0.0001527631,0.00004047091,0.0002494969,0.0001527426,0.00005640648],"domain_scores_gemma":[0.9991229,0.0005008713,0.00009238136,0.0000849898,0.0001501832,0.00004857211],"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":[0.0001017236,0.000189822,0.001744738,0.0001433054,0.000146574,0.0003255553,0.000300719,0.8035117,0.002666893,0.05541411,0.001139504,0.1343154],"study_design_scores_gemma":[0.000003543099,0.00002034025,0.0001271715,0.000007432916,0.0000125705,0.00001381225,0.00001069859,0.983724,0.0003153129,0.01533797,0.0004219136,0.000005189635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009026225,0.0002067319,0.9888814,0.0002513934,0.00001484996,0.00006838573,0.0001028223,0.0003323879,0.001115841],"genre_scores_gemma":[0.5100116,0.000460702,0.4853387,0.0002341462,0.0001012121,0.0003697953,0.0005218922,0.00007123662,0.002890783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01197703,"threshold_uncertainty_score":0.02381468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0693269003755229,"score_gpt":0.4008125750963586,"score_spread":0.3314856747208357,"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."}}