{"id":"W2943608204","doi":"10.3982/qe1060","title":"Jump factor models in large cross‐sections","year":2019,"lang":"en","type":"article","venue":"Quantitative Economics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Jump; Estimator; Econometrics; Factor analysis; Mathematics; Heteroscedasticity; Statistics; Null hypothesis; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003165104,0.0001830883,0.0004280944,0.0002995893,0.0000819359,0.0001395247,0.0001960263,0.0001168732,0.00101667],"category_scores_gemma":[0.00004766529,0.0002265747,0.000123993,0.0001650775,0.0000613739,0.001127937,0.00005435221,0.0001754353,0.002491408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001829273,"about_ca_system_score_gemma":0.00004148997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002997119,"about_ca_topic_score_gemma":0.000337026,"domain_scores_codex":[0.998472,0.00001448059,0.0006444092,0.0004734509,0.00001428346,0.0003813353],"domain_scores_gemma":[0.9992874,0.00008258146,0.0002726987,0.0002770712,0.00002499012,0.00005529299],"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":[0.0000221706,0.00007228182,0.1253752,0.00001467955,0.00001871119,5.726426e-7,0.0004823365,0.004127014,0.000003473335,0.8697702,0.00009065541,0.00002275774],"study_design_scores_gemma":[0.001220989,0.0001943389,0.4013531,0.00001629748,0.000001534376,8.538668e-7,0.0004027819,0.06564244,0.00004377444,0.5098386,0.02080139,0.0004838686],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8291551,0.0005061458,0.0008983388,0.0001219947,0.0008022857,0.0002558942,0.0004908118,0.00002731308,0.1677421],"genre_scores_gemma":[0.9960228,0.0004346424,0.0008850947,0.0002702292,0.00003927391,0.00002968825,0.00002555769,0.00003040073,0.002262355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3599315,"threshold_uncertainty_score":0.9998965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06776226396943172,"score_gpt":0.2727294538677635,"score_spread":0.2049671898983318,"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."}}