{"id":"W7117372915","doi":"10.54097/xcdv2r97","title":"Framework for Forecasting and Timing Rare Equity Events","year":2025,"lang":"","type":"article","venue":"Highlights in Business Economics and Management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Equity (law); Financial market; Support vector machine; Risk management; Rare events; Pipeline (software); Feature (linguistics); Nonlinear system","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":[0.005523946,0.0005202298,0.0009268563,0.00121135,0.0006874082,0.0008476514,0.0007914662,0.000293891,0.00004125517],"category_scores_gemma":[0.001641095,0.0004975243,0.0001117953,0.001060019,0.0002038745,0.0005032943,0.003012108,0.000162589,0.000003649936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002487733,"about_ca_system_score_gemma":0.00009744745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004871617,"about_ca_topic_score_gemma":0.0001152085,"domain_scores_codex":[0.9956436,0.0001703457,0.001551769,0.001606948,0.000228292,0.0007990747],"domain_scores_gemma":[0.9948557,0.003399928,0.0006149229,0.0007584719,0.0002214717,0.0001494778],"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":[0.0001860782,0.00006042053,0.0006441961,0.0006285592,0.00008968442,0.000007886355,0.0001861788,0.0007401951,4.754302e-7,0.6159707,0.0002851301,0.3812005],"study_design_scores_gemma":[0.001943399,0.00004839161,0.04993025,0.001962435,0.0001799442,0.000007444907,0.0004500963,0.1005286,0.00002009587,0.5563355,0.287957,0.0006368222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1582807,0.00371064,0.7401807,0.04769789,0.01155154,0.005397554,0.00008861024,0.00007212548,0.03302017],"genre_scores_gemma":[0.2975997,0.07002097,0.6212581,0.001265014,0.0004399486,0.000614509,0.00001642844,0.0001071741,0.008678121],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3805636,"threshold_uncertainty_score":0.9997476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1541129419248952,"score_gpt":0.3920595454282912,"score_spread":0.237946603503396,"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."}}