{"id":"W3125868777","doi":"","title":"Worldscope meets Compustat: A Comparison of Financial Databases","year":2005,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Financial Reporting and Valuation Research","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Database; Accounting; Quality (philosophy); Outcome (game theory); Actuarial science; Data source; Finance; Business; Economics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0125375,0.0004881123,0.0007673223,0.02609143,0.0007669239,0.00649473,0.001260283,0.0009073988,0.003603071],"category_scores_gemma":[0.0759106,0.0003788695,0.0007288154,0.04345314,0.0005577328,0.005282041,0.003039869,0.0006880692,0.001053215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002713441,"about_ca_system_score_gemma":0.002915022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04628801,"about_ca_topic_score_gemma":0.06135431,"domain_scores_codex":[0.9781279,0.006788759,0.003357786,0.00181446,0.008958889,0.0009521607],"domain_scores_gemma":[0.9114446,0.05327989,0.01096794,0.007845391,0.01453115,0.001930952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002762162,0.0003973785,0.6631078,0.002661384,0.002358077,0.0007110725,0.004572498,0.004104345,0.002180254,0.03579108,0.08662244,0.1947316],"study_design_scores_gemma":[0.0002821277,0.0003154956,0.7937148,0.001563137,0.0009279424,0.001272419,0.01090314,0.005992295,0.003615995,0.005942202,0.1752814,0.0001890209],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7736191,0.0180196,0.006317867,0.003261561,0.0003183998,0.0003534029,0.1506766,0.0005658902,0.0468676],"genre_scores_gemma":[0.7536198,0.006040508,0.01742974,0.0005623801,0.0001871736,0.0002901538,0.2189662,0.0003852504,0.002518825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04628801,"threshold_uncertainty_score":0.0920372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1188530816752489,"score_gpt":0.3963654998500779,"score_spread":0.277512418174829,"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."}}