{"id":"W2151921280","doi":"10.1017/s0022109000002349","title":"Multifactor Evaluation of Style Rotation","year":2005,"lang":"en","type":"article","venue":"Journal of Financial and Quantitative Analysis","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sharpe ratio; Rotation (mathematics); Style (visual arts); Equity (law); Econometrics; Attribution; Economics; Logistic regression; Computer science; Psychology; Artificial intelligence; Financial economics; Machine learning; Social psychology; Portfolio; Geography; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.00155113,0.00008984128,0.0004896166,0.0005597425,0.00005713553,0.00002536483,0.00007383838,0.00005244351,0.0002078871],"category_scores_gemma":[0.0006346302,0.00008303107,0.0002284046,0.0005501874,0.00006781374,0.0004969257,0.00001068263,0.0000794182,0.000009404484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004890135,"about_ca_system_score_gemma":0.00005780354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001040423,"about_ca_topic_score_gemma":0.0001249948,"domain_scores_codex":[0.9988011,0.00004440168,0.0008155389,0.0001238647,0.000115775,0.00009933708],"domain_scores_gemma":[0.9982325,0.00006685882,0.001176546,0.00007479868,0.0004087807,0.00004045495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002549039,0.0004329728,0.1635517,0.0000502726,0.001151832,0.000002296988,0.004464188,0.005084339,0.0007851161,0.7857266,0.0006279303,0.03786781],"study_design_scores_gemma":[0.0009645916,0.000408022,0.9333869,0.00002333459,0.000564254,0.000001135627,0.0003536253,0.03345435,0.0003371317,0.02720202,0.003142053,0.0001626492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881666,0.003983604,0.00505563,0.0002637998,0.00008665121,0.00007317089,0.00003985869,0.000001882247,0.002328814],"genre_scores_gemma":[0.9951095,0.0004391883,0.004257511,0.0000543347,0.00007887749,0.00000225853,0.000004103299,0.000004231405,0.00004999045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7698351,"threshold_uncertainty_score":0.3385909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0706652242607427,"score_gpt":0.2979612574384853,"score_spread":0.2272960331777426,"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."}}