{"id":"W1881782813","doi":"10.2139/ssrn.2285210","title":"Analystss Earnings Forecasts and Other Comprehensive Income","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Royal University","funders":"","keywords":"Earnings; Economics; Business; Actuarial science; Econometrics; Accounting","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":[0.00103313,0.0003787747,0.0003464314,0.00392575,0.0003505701,0.002204766,0.0004169273,0.0006873345,0.01532637],"category_scores_gemma":[0.01723953,0.0001506421,0.0003007947,0.003030106,0.0002209796,0.001862225,0.0006807476,0.0009292415,0.00363033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007414306,"about_ca_system_score_gemma":0.0008070681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01849306,"about_ca_topic_score_gemma":0.02817447,"domain_scores_codex":[0.9993277,0.00007130288,0.00005496246,0.0001122212,0.0003482388,0.00008574422],"domain_scores_gemma":[0.9899818,0.00338456,0.003222571,0.0006495443,0.001944011,0.0008174397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008223897,0.0003001931,0.7818509,0.0001096411,0.0003129423,0.0003436563,0.0005802306,0.0162694,0.0005029025,0.01673264,0.07175498,0.1104202],"study_design_scores_gemma":[0.00002890851,0.0002302528,0.9320098,0.00009351952,0.0001191783,0.0002343398,0.0005555176,0.02049346,0.001021567,0.01548823,0.02964192,0.00008328164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8434041,0.001781855,0.005890787,0.002095264,0.0004144338,0.00005947742,0.06520008,0.001152122,0.080002],"genre_scores_gemma":[0.9385348,0.0005760697,0.001016023,0.00006619229,0.0002143591,0.00002393365,0.02575662,0.00005729656,0.03375469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01849306,"threshold_uncertainty_score":0.05127186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007093072577772316,"score_gpt":0.2047911259848244,"score_spread":0.1976980534070521,"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."}}