{"id":"W2340485753","doi":"10.1111/1475-679x.12116","title":"Causal Inference in Accounting Research","year":2016,"lang":"en","type":"article","venue":"Journal of Accounting Research","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":333,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"Causal inference; Accounting research; Causal model; Accounting; Focus (optics); Observational study; Inference; Econometrics; Computer science; Management science; Economics; Artificial intelligence; Mathematics; Statistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1618503,0.001362299,0.002268826,0.009539938,0.003095539,0.008793261,0.003164426,0.004839107,0.01051531],"category_scores_gemma":[0.3950306,0.001176067,0.001995253,0.007297498,0.02186409,0.01287786,0.005317789,0.007207467,0.0006084551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00584307,"about_ca_system_score_gemma":0.006689235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004003907,"about_ca_topic_score_gemma":0.002221581,"domain_scores_codex":[0.7937831,0.1833754,0.004075475,0.00693626,0.01039241,0.001437337],"domain_scores_gemma":[0.3048489,0.6542508,0.01625804,0.01510807,0.008663034,0.0008712161],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004769025,0.00006216732,0.003258261,0.0007706548,0.0003097733,0.0001223776,0.0008427879,0.004037421,0.00004549247,0.964541,0.001880287,0.02408212],"study_design_scores_gemma":[0.00003367786,0.00002327047,0.0006107626,0.0004331525,0.0000584764,0.00004565536,0.0003022913,0.00533463,0.0001112136,0.9898703,0.003158992,0.00001760676],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02907924,0.0335439,0.7840142,0.08073501,0.003095472,0.001265129,0.001093666,0.0003549685,0.06681839],"genre_scores_gemma":[0.8299128,0.01356618,0.1432424,0.006532261,0.002210157,0.001422936,0.0004454358,0.00007106875,0.002596766],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8381497,"threshold_uncertainty_score":0.8559564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06703160552590866,"score_gpt":0.3652183836835421,"score_spread":0.2981867781576335,"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."}}