{"id":"W1507326277","doi":"10.1080/19388160.2011.576937","title":"Visitor and Resident Images of Qingdao, China, as a Tourism Destination","year":2011,"lang":"en","type":"article","venue":"Journal of China Tourism Research","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visitor pattern; Tourism; China; Cognition; Spearman's rank correlation coefficient; Psychology; Destination image; Test (biology); Advertising; Geography; Tourist attraction; Destinations; Computer science; Business; Mathematics; Statistics; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0003407258,0.0001528093,0.0001013594,0.0005574591,0.0003764959,0.0005409734,0.0001048668,0.0001363963,0.001341433],"category_scores_gemma":[0.001273864,0.00008055139,0.0001572217,0.0004082694,0.0003209362,0.000304011,0.0003715517,0.0001903678,0.00006025915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004722893,"about_ca_system_score_gemma":0.0002325331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201713,"about_ca_topic_score_gemma":0.04474021,"domain_scores_codex":[0.9998891,0.00003468575,0.000009297808,0.000009894701,0.00003274702,0.00002419214],"domain_scores_gemma":[0.999245,0.0001408835,0.0003502961,0.00002527031,0.0001017018,0.0001368037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001437394,0.0000363723,0.9770268,0.00004949635,0.00003945384,0.0002180508,0.01512184,0.0001025333,0.001397615,0.00009572551,0.0002495086,0.005518853],"study_design_scores_gemma":[0.000001726388,0.0000449057,0.989378,0.000004674353,0.000006693217,0.00008220782,0.01008477,0.00008812045,0.00005722258,0.000009203244,0.0002376961,0.000004794026],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995859,0.0000199121,0.00001273982,0.00001183923,8.634003e-7,0.000001407743,0.00002789647,4.382758e-7,0.0003390438],"genre_scores_gemma":[0.9996927,0.00003100685,0.00002669748,0.000006811016,0.00000127745,0.000001647207,0.00005091031,3.481463e-7,0.0001886063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201713,"threshold_uncertainty_score":0.04010773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06404874699947392,"score_gpt":0.3958239462975841,"score_spread":0.3317751992981101,"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."}}