{"id":"W4376876763","doi":"10.18111/wtobarometereng.2023.21.1.2","title":"UNWTO World Tourism Barometer and Statistical Annex, May 2023","year":2023,"lang":"en","type":"article","venue":"UNWTO World Tourism Barometer","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Geography; Tourism; Pandemic; Destinations; China; Middle East; Coronavirus disease 2019 (COVID-19); Socioeconomics; Economics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001467623,0.001073171,0.0005042804,0.002269717,0.0008758039,0.004372687,0.00103495,0.0014206,0.1505159],"category_scores_gemma":[0.006131937,0.0005973502,0.0005637825,0.004932183,0.0003465158,0.002018268,0.001377407,0.002722841,0.1654058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698422,"about_ca_system_score_gemma":0.004895393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04979529,"about_ca_topic_score_gemma":0.03867009,"domain_scores_codex":[0.9989912,0.00009371344,0.0001301281,0.0001030954,0.0004946475,0.0001871444],"domain_scores_gemma":[0.9971851,0.0002922692,0.0002965472,0.0001817988,0.001784597,0.0002595757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005358872,0.00001650582,0.0004800458,0.0001388594,0.000002865164,0.0000158787,0.00001272841,0.0001085869,0.00005656896,0.001077317,0.9862869,0.01175015],"study_design_scores_gemma":[0.00002274204,0.00001640864,0.006953002,0.0002582383,0.000002280571,0.00001492004,0.00006059549,0.0001571419,0.00009493345,0.000462385,0.9919402,0.00001721192],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001972697,0.001758552,0.001653673,0.007618457,0.01805918,0.001163964,0.5401999,0.002342564,0.4252309],"genre_scores_gemma":[0.008711758,0.003077983,0.002909904,0.004980646,0.001859027,0.002222859,0.3229569,0.001390222,0.6518907],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1505159,"threshold_uncertainty_score":0.5035259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03681325465404452,"score_gpt":0.3417414181546277,"score_spread":0.3049281635005832,"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."}}