{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009264533,0.0008217362,0.0004267034,0.002266719,0.002578291,0.007561019,0.001483356,0.002183021,0.02124728],"category_scores_gemma":[0.01518476,0.0003254281,0.0006887646,0.003757109,0.001046477,0.00501803,0.007249512,0.004459057,0.008543713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004336381,"about_ca_system_score_gemma":0.03540577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07571588,"about_ca_topic_score_gemma":0.09105664,"domain_scores_codex":[0.9917579,0.001720996,0.0003320764,0.0002286574,0.004886957,0.001073353],"domain_scores_gemma":[0.9889429,0.00238579,0.0006234816,0.0009358394,0.004900783,0.002211194],"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":[0.00005941626,0.0001320966,0.003531737,0.000251756,0.0000157766,0.00008559549,0.0002756111,0.0007128099,0.0003043199,0.04831996,0.8826999,0.06361099],"study_design_scores_gemma":[0.00001522968,0.0000492015,0.007490767,0.0006004978,0.00000857999,0.00005589646,0.001610171,0.001792509,0.0007679957,0.01150012,0.9760769,0.00003216384],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01354772,0.006652853,0.01383385,0.2968199,0.007612129,0.002062362,0.07697028,0.001759186,0.5807418],"genre_scores_gemma":[0.1855893,0.03579974,0.09212521,0.05137767,0.003446725,0.005409635,0.2481036,0.001880348,0.3762678],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07571588,"threshold_uncertainty_score":0.1505504,"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."}}