{"id":"W4393210524","doi":"10.2139/ssrn.2803745","title":"CEO Networks and Information Aggregation: Evidence from Management Forecast Accuracy","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Aggregate (composite); Relation (database); Earnings; Forecast error; Econometrics; Business; Macro; Economics; Industrial organization; Computer science; Accounting; Data mining","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":[0.008359663,0.000296611,0.0004966758,0.00193717,0.0006169619,0.002691174,0.0006569673,0.001361781,0.004227093],"category_scores_gemma":[0.1002723,0.0003274319,0.0003523839,0.002558088,0.0005891304,0.003003004,0.001053898,0.001111689,0.0008780387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004808474,"about_ca_system_score_gemma":0.0003697746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007342673,"about_ca_topic_score_gemma":0.006098082,"domain_scores_codex":[0.9970138,0.001209786,0.0003089251,0.0004976558,0.0007174836,0.000252278],"domain_scores_gemma":[0.7510048,0.1849073,0.04352614,0.01026323,0.00789008,0.002408397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007904969,0.0002197852,0.9620165,0.00006008575,0.0004161449,0.00009587704,0.0006637599,0.005274532,0.0002515683,0.001539727,0.002577209,0.02609432],"study_design_scores_gemma":[0.00008990731,0.0002104712,0.9703072,0.00008267592,0.0003718763,0.0001029951,0.0008715412,0.01643853,0.0006034955,0.008256609,0.002619714,0.00004486823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988049,0.001108935,0.001462579,0.001637506,0.00005632009,0.00001498795,0.0007975191,0.00002535934,0.006847856],"genre_scores_gemma":[0.9982639,0.0003405387,0.0002287898,0.00007192843,0.0001225841,0.00000567218,0.0005645039,0.000004557255,0.0003975728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008359663,"threshold_uncertainty_score":0.04421061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011344154086071,"score_gpt":0.1981652869833796,"score_spread":0.1880518454425189,"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."}}