{"id":"W4226126191","doi":"10.1177/0193841x221085355","title":"Analyzing the Nexus Between Geopolitical Risk, Policy Uncertainty, and Tourist Arrivals: Evidence From the United States","year":2022,"lang":"en","type":"article","venue":"Evaluation Review","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Nexus (standard); Geopolitics; Tourism; Political science; Economics; Regional science; Geography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":{"nature":"Expression of concern","reason":"Concerns/Issues about Authorship/Affiliation;Lack of Approval from Company/Institution;","date":"5/11/2023 0:00","openalex_flagged":false},"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001185114,0.0002599591,0.0003068203,0.001661307,0.0003178589,0.001180841,0.0002643848,0.0003102172,0.0016238],"category_scores_gemma":[0.00494088,0.0001432603,0.0006564855,0.003611841,0.0003929886,0.0007901012,0.0007168145,0.0008777856,0.0001353639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005356294,"about_ca_system_score_gemma":0.001337043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04237693,"about_ca_topic_score_gemma":0.06092035,"domain_scores_codex":[0.9996371,0.0001387071,0.00003999007,0.00005331529,0.00008592248,0.00004483043],"domain_scores_gemma":[0.994942,0.002725341,0.001436469,0.0001411983,0.000627992,0.0001269798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002031663,0.0001909738,0.8942965,0.002324718,0.001797987,0.0004890017,0.0009675635,0.003858581,0.0002383337,0.008865528,0.006392311,0.08037534],"study_design_scores_gemma":[0.00002137754,0.0001878555,0.9563416,0.001690183,0.001369003,0.0001681269,0.006776944,0.004585469,0.0004381372,0.004047795,0.02431881,0.00005468299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8907594,0.08126471,0.002330142,0.005880937,0.0002636671,0.00006445907,0.00463917,0.000018303,0.01477921],"genre_scores_gemma":[0.9602813,0.03642889,0.0004740666,0.0004759785,0.00009433362,0.00001692416,0.001709447,0.000005244349,0.0005138193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04237693,"threshold_uncertainty_score":0.08426052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068698492901642,"score_gpt":0.3450513100099599,"score_spread":0.2381814607197958,"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."}}