{"id":"W4200359138","doi":"10.22617/spr210438-2","title":"Big Data for Better Tourism Policy, Management, and Sustainable Recovery from COVID-19","year":2021,"lang":"en","type":"report","venue":"","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sustainable Development Technology Canada; Steno Diabetes Center Copenhagen; Asian Development Bank","keywords":"Big data; Tourism; Coronavirus disease 2019 (COVID-19); Business; Private sector; 2019-20 coronavirus outbreak; Measure (data warehouse); Economics; Geography; Economic growth; Computer science; Data mining","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004193025,0.0002949459,0.0005317222,0.0005730782,0.00103346,0.001227842,0.001868864,0.0004773698,0.001905973],"category_scores_gemma":[0.006207541,0.0002999722,0.000142725,0.0004938658,0.0003680298,0.0005585384,0.004362543,0.0003536713,0.00003570525],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445185,"about_ca_system_score_gemma":0.01058689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4736889,"about_ca_topic_score_gemma":0.01752957,"domain_scores_codex":[0.9949495,0.0002663497,0.0003570896,0.001297681,0.001891913,0.001237475],"domain_scores_gemma":[0.9961266,0.000868568,0.0002165187,0.001639637,0.0005282796,0.0006203825],"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":[0.00001889991,0.00004187854,0.0001762164,0.0004396511,0.0004094804,0.002145709,0.0001614192,3.782659e-7,2.848326e-7,0.004166235,0.9676492,0.02479067],"study_design_scores_gemma":[0.0003890423,0.00002229691,0.0001320615,0.00004051971,0.000138701,0.000001800219,0.01238861,0.000002513999,0.000001688532,0.02818351,0.9583528,0.0003464226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001313993,0.001951413,0.001707479,0.04013626,0.001226921,0.001768452,0.001695328,0.0001413538,0.9512414],"genre_scores_gemma":[0.0003381039,0.02215651,0.004058159,0.002742021,0.009722299,0.00009606151,0.002528263,0.00006709233,0.9582915],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4561594,"threshold_uncertainty_score":0.9999452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1704870009274597,"score_gpt":0.4250218711287428,"score_spread":0.2545348702012831,"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."}}