{"id":"W1989808110","doi":"10.1017/s0022109010000451","title":"Seasonality in the Cross Section of Stock Returns: The International Evidence","year":2010,"lang":"en","type":"article","venue":"Journal of Financial and Quantitative Analysis","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Predictability; Stock (firearms); Economics; Financial economics; Seasonality; Stock market; Econometrics; Monetary economics; Geography; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002664139,0.00008000047,0.0003177955,0.0001542512,0.00009777831,0.00009055754,0.0003101309,0.00005711044,0.00006305829],"category_scores_gemma":[0.001412954,0.0000492209,0.0002250533,0.0006607639,0.00020209,0.0004651236,0.00002627896,0.0003283896,0.000001504378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001792474,"about_ca_system_score_gemma":0.00004881151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004346487,"about_ca_topic_score_gemma":0.001299568,"domain_scores_codex":[0.998967,0.00004934194,0.0006619412,0.000121729,0.0001033912,0.00009660912],"domain_scores_gemma":[0.9984964,0.000322471,0.0008580068,0.000120004,0.0001832973,0.00001980849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001181289,0.00006774495,0.6329355,0.00001101296,0.0001314539,0.000003533348,0.001499253,0.00006371471,0.0002014378,0.3643099,0.000324273,0.000333963],"study_design_scores_gemma":[0.0001594621,0.0001360221,0.9602183,0.00001963677,0.00005170655,0.000004332973,0.0002555795,0.000865499,0.00002953533,0.03528706,0.002913385,0.00005944144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942052,0.001476725,0.000645205,0.001924981,0.0004295634,0.00005796292,0.00002954228,9.766534e-7,0.001229817],"genre_scores_gemma":[0.9986073,0.0006272781,0.0003175007,0.0002242631,0.0001680568,0.000002870703,0.000001112235,0.000002449617,0.00004916435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3290229,"threshold_uncertainty_score":0.200717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07095115020317103,"score_gpt":0.3140690492664164,"score_spread":0.2431178990632454,"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."}}