{"id":"W3121512853","doi":"","title":"The Return Premiums to Accruals Quality","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Decile; Accrual; Econometrics; Portfolio; Economics; Earnings; Actuarial science; Financial economics; Statistics; Mathematics; Finance","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":[0.003357147,0.0004243667,0.0004548337,0.001800539,0.0001336009,0.001648042,0.0005074292,0.0008468437,0.004452421],"category_scores_gemma":[0.04148463,0.000203149,0.0006503549,0.001201542,0.0006439667,0.00152658,0.001056882,0.001287638,0.000709549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005459431,"about_ca_system_score_gemma":0.000275666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001153676,"about_ca_topic_score_gemma":0.0006217044,"domain_scores_codex":[0.9984398,0.0002461474,0.0001383728,0.0002182445,0.0007753711,0.0001820333],"domain_scores_gemma":[0.9544799,0.01807152,0.01908302,0.003698445,0.002696551,0.001970556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009307713,0.0003928225,0.8697445,0.0001276671,0.0003334732,0.0003613278,0.0003379425,0.01543392,0.009440712,0.01152392,0.001510633,0.08986239],"study_design_scores_gemma":[0.00002359,0.0002778427,0.9746782,0.00001692567,0.00006412976,0.0003374022,0.00006431375,0.01100544,0.001998458,0.01073017,0.000760539,0.00004289943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98677,0.0007918607,0.006324012,0.0004527706,0.00004045086,0.00003255462,0.0004919763,0.0001642396,0.004932137],"genre_scores_gemma":[0.998578,0.00009353612,0.0004112961,0.00004236062,0.00003666192,0.000004105295,0.0002028998,0.0000132843,0.0006178211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004452421,"threshold_uncertainty_score":0.0177545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05159870582377685,"score_gpt":0.2691704332916657,"score_spread":0.2175717274678888,"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."}}