{"id":"W4313890734","doi":"10.1057/s41267-022-00586-8","title":"Correction: Income inequality, social cohesion, and crime against businesses: Evidence from a global sample of firms","year":2023,"lang":"en","type":"article","venue":"Journal of International Business Studies","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Cohesion (chemistry); Economic inequality; Inequality; International business; Sample (material); Economics; Social inequality; Management; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009217752,0.00009400945,0.0003017067,0.0001463014,0.0002690037,0.00006653331,0.0002319556,0.00004610012,0.00009786295],"category_scores_gemma":[0.004925665,0.00008248814,0.0000620537,0.0005474234,0.0002217135,0.0004701756,0.0001959582,0.00006977733,0.0000124305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003401899,"about_ca_system_score_gemma":0.0002910609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322112,"about_ca_topic_score_gemma":0.0008959215,"domain_scores_codex":[0.9986377,0.00006951392,0.0005778781,0.0001212362,0.0004719355,0.00012172],"domain_scores_gemma":[0.9966049,0.0007679239,0.0005496939,0.00004403161,0.001989604,0.00004381907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002858836,0.000109833,0.90409,0.00007549472,0.000613239,0.0000261299,0.02237158,0.0002602382,0.0001473446,0.001295646,0.01682014,0.05390448],"study_design_scores_gemma":[0.0003144694,0.00001210988,0.9776133,0.0004323543,0.00002104205,0.000003583957,0.01170695,0.0000550659,0.000009340501,0.001456173,0.008279987,0.00009562719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795721,0.0008179356,0.0004954745,0.01104044,0.007124414,0.00006397735,0.00003624208,0.00002390249,0.0008255129],"genre_scores_gemma":[0.9903066,0.008138785,0.0003237666,0.0001563883,0.0008285758,0.000003319682,0.000005488335,0.000004323707,0.0002327788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07352331,"threshold_uncertainty_score":0.5896837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.113432803194215,"score_gpt":0.3928530089262366,"score_spread":0.2794202057320215,"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."}}