{"id":"W2953999747","doi":"10.5539/ijef.v11n7p110","title":"Exporting Transparency Through Mergers","year":2019,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Sherbrooke","funders":"","keywords":"Openness to experience; Proxy (statistics); Transparency (behavior); Competition (biology); Language change; International economics; Economics; Monetary economics; Capital (architecture); Mergers and acquisitions; Business; Market economy; Finance; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003088017,0.00003746554,0.00009458368,0.00003577649,0.0000407327,0.0000463485,0.000156037,0.00002380952,0.0002382948],"category_scores_gemma":[0.00001741177,0.00003960779,0.00004549895,0.00001450157,0.00003026705,0.0003320838,0.00001145294,0.00005005545,0.00002491156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008469947,"about_ca_system_score_gemma":0.0001208593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000638572,"about_ca_topic_score_gemma":0.00009021939,"domain_scores_codex":[0.999497,0.00000724316,0.0003098351,0.00006723269,0.0000424643,0.00007622194],"domain_scores_gemma":[0.9995692,0.00002398361,0.0002909745,0.00002818719,0.00006711832,0.00002056077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001033977,0.00006645871,0.03096041,0.000004054759,0.0001401155,0.00001375318,0.02088884,0.008021052,0.00003692303,0.6511999,0.0004783646,0.2880868],"study_design_scores_gemma":[0.0004356159,0.0000219734,0.006602849,0.00002764956,0.000002788682,0.000008334508,0.001576176,0.0006136019,0.00002497176,0.00520772,0.9853827,0.00009558789],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643357,0.0001418913,0.0000826859,0.002811372,0.002185504,0.00002776141,0.000002495561,0.000001587192,0.03041099],"genre_scores_gemma":[0.9859887,0.01153389,0.0008829318,0.0002692675,0.0001768852,5.168217e-7,5.501396e-7,0.000002742425,0.001144491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9849043,"threshold_uncertainty_score":0.2609161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0287038089057416,"score_gpt":0.285894374327188,"score_spread":0.2571905654214464,"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."}}