{"id":"W2805007726","doi":"10.5539/ibr.v11n6p151","title":"Measuring the Effectiveness of National Enforcers in the IFRS Context: A Proactive Approach","year":2018,"lang":"en","type":"article","venue":"International Business Research","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Enforcement; Audit; Accounting; Context (archaeology); Business; Quality (philosophy); Index (typography); Political science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01565565,0.0005706977,0.0007400566,0.005710085,0.001903877,0.007025318,0.001476881,0.001670793,0.002785507],"category_scores_gemma":[0.02984676,0.000382903,0.000554455,0.005424838,0.003280941,0.003334668,0.004078452,0.001544295,0.0004686371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003691271,"about_ca_system_score_gemma":0.002911058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00791402,"about_ca_topic_score_gemma":0.0104642,"domain_scores_codex":[0.9827074,0.007101248,0.001624723,0.002247941,0.005032109,0.001286574],"domain_scores_gemma":[0.9540793,0.01308599,0.02125164,0.005383873,0.004397477,0.00180172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002070337,0.0006978583,0.8675522,0.0002933623,0.0002515505,0.0003875927,0.01826642,0.002726028,0.00201017,0.02543003,0.001054851,0.08112291],"study_design_scores_gemma":[0.000021704,0.0006798736,0.9424625,0.0003552192,0.0002006904,0.0002610604,0.02941319,0.006365238,0.002321854,0.006627362,0.01122701,0.00006421459],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9455757,0.0006352603,0.009501903,0.0006484746,0.00003216137,0.0003197514,0.0002120579,0.00004987364,0.0430248],"genre_scores_gemma":[0.9954154,0.0001399439,0.002897929,0.00006382236,0.00002270319,0.00006389507,0.0001255231,0.000006027968,0.001264815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01565565,"threshold_uncertainty_score":0.08279598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06225966774772155,"score_gpt":0.3178326262841462,"score_spread":0.2555729585364246,"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."}}