{"id":"W4226352575","doi":"10.1079/tourism.2022.0019","title":"Supporting Informed Destination Development Using Visitor Intelligence","year":2022,"lang":"en","type":"article","venue":"Tourism Cases","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University","funders":"","keywords":"Visitor pattern; Marketing; Tourism; Logo (programming language); Destinations; Excellence; Market segmentation; Business; Public relations; Advertising; Geography; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00587727,0.0005841183,0.0003060764,0.001918366,0.002451835,0.009127418,0.001873673,0.001165655,0.008810051],"category_scores_gemma":[0.0113433,0.0003717572,0.0003639985,0.001354825,0.002232785,0.00544327,0.009151298,0.001218199,0.001483528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002435415,"about_ca_system_score_gemma":0.003755005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0131764,"about_ca_topic_score_gemma":0.02283692,"domain_scores_codex":[0.9945847,0.003722823,0.0001359317,0.0004417495,0.0006920291,0.0004227655],"domain_scores_gemma":[0.9923682,0.003540925,0.0006397196,0.001634436,0.0007562425,0.001060417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005214312,0.001811685,0.08551494,0.0007949814,0.0001225817,0.003983318,0.1556617,0.02040243,0.00692228,0.1149101,0.04218777,0.5671668],"study_design_scores_gemma":[0.0001338387,0.0009749618,0.03043435,0.0009527748,0.0001074949,0.001683423,0.2253708,0.1021022,0.006383653,0.07056252,0.5610361,0.0002578883],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4875612,0.0003478944,0.1415724,0.0100966,0.00009298281,0.001493279,0.0006386171,0.002127021,0.35607],"genre_scores_gemma":[0.9242551,0.0002424015,0.06079807,0.0002149023,0.00001472271,0.000287902,0.000493534,0.0001269483,0.01356636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0131764,"threshold_uncertainty_score":0.03108233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08735002772921698,"score_gpt":0.415657453666308,"score_spread":0.328307425937091,"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."}}